def main():
args = parse_options()
for port in args.ports:
client = Recommender(args.host, int(port), args.name)
try:
result = client.get_all_rows()
logging.info('{0}:{1} ... {2}'.format(args.host, port, result))
except:
logging.exception('{0}:{1}'.format(args.host, port))
def main():
args = parse_options()
for port in args.ports:
client = Recommender(args.host, int(port), args.name)
try:
result = client.get_all_rows()
logging.info('{0}:{1} ... {2}'.format(args.host, port, result))
except:
logging.exception('{0}:{1}'.format(args.host, port))
def main():
args = parse_options()
for port in args.ports:
client = Recommender(args.host, int(port), args.name)
d = Datum({'key': 1.0})
try:
result = client.update_row(args.id, d)
logging.info('{0}:{1} ... {2}'.format(args.host, port, result))
except:
logging.exception('{0}:{1}'.format(args.host, port))
def main():
args = parse_options()
for port in args.ports:
client = Recommender(args.host, int(port), args.name)
d = Datum({"key": 1.0})
try:
result = client.update_row(args.id, d)
logging.info("{0}:{1} ... {2}".format(args.host, port, result))
except:
logging.exception("{0}:{1}".format(args.host, port))
def setUp(self):
self.config = {
"method": "inverted_index",
"converter": {
"string_filter_types": {},
"string_filter_rules": [],
"num_filter_types": {},
"num_filter_rules": [],
"string_types": {},
"string_rules": [{"key": "*", "type": "str", "sample_weight": "bin", "global_weight": "bin"}],
"num_types": {},
"num_rules": [{"key": "*", "type": "num"}]
},
"parameter": {}
}
TestUtil.write_file('config_recommender.json', json.dumps(self.config))
self.srv = TestUtil.fork_process('recommender', port, 'config_recommender.json')
try:
self.cli = Recommender(host, port, "name")
except:
TestUtil.kill_process(self.srv)
raise
def setUp(self):
self.config = {
"method": "inverted_index",
"converter": {
"string_filter_types": {},
"string_filter_rules": [],
"num_filter_types": {},
"num_filter_rules": [],
"string_types": {},
"string_rules": [{"key": "*", "type": "str", "sample_weight": "bin", "global_weight": "bin"}],
"num_types": {},
"num_rules": [{"key": "*", "type": "num"}]
},
"parameter": {}
}
TestUtil.write_file('config_recommender.json', json.dumps(self.config))
self.srv = TestUtil.fork_process('recommender', port, 'config_recommender.json')
try:
self.cli = Recommender(host, port, "name")
except:
TestUtil.kill_process(self.srv)
raise
class RecommenderTest(unittest.TestCase):
def setUp(self):
self.config = {
"method": "inverted_index",
"converter": {
"string_filter_types": {},
"string_filter_rules": [],
"num_filter_types": {},
"num_filter_rules": [],
"string_types": {},
"string_rules": [{"key": "*", "type": "str", "sample_weight": "bin", "global_weight": "bin"}],
"num_types": {},
"num_rules": [{"key": "*", "type": "num"}]
},
"parameter": {}
}
TestUtil.write_file('config_recommender.json', json.dumps(self.config))
self.srv = TestUtil.fork_process('recommender', port, 'config_recommender.json')
try:
self.cli = Recommender(host, port, "name")
except:
TestUtil.kill_process(self.srv)
raise
def tearDown(self):
TestUtil.kill_process(self.srv)
def test_get_client(self):
self.assertTrue(isinstance(self.cli.get_client(), msgpackrpc.client.Client))
def test_get_config(self):
config = self.cli.get_config()
self.assertEqual(json.dumps(json.loads(config), sort_keys=True), json.dumps(self.config, sort_keys=True))
def test_complete_row(self):
self.cli.clear_row("complete_row")
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.cli.update_row("complete_row", d)
d1 = self.cli.complete_row_from_id("complete_row")
d2 = self.cli.complete_row_from_datum(d)
def test_similar_row(self):
self.cli.clear_row("similar_row")
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.cli.update_row("similar_row", d)
s1 = self.cli.similar_row_from_id("similar_row", 10)
s2 = self.cli.similar_row_from_datum(d, 10)
def test_decode_row(self):
self.cli.clear_row("decode_row")
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.cli.update_row("decode_row", d)
decoded_row = self.cli.decode_row("decode_row")
self.assertEqual(json.dumps(d.string_values), json.dumps(decoded_row.string_values))
self.assertEqual(json.dumps(d.num_values), json.dumps(decoded_row.num_values))
def test_get_row(self):
self.cli.clear()
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.cli.update_row("get_row", d)
row_names = self.cli.get_all_rows()
self.assertEqual(row_names, ["get_row"])
def test_clear(self):
self.cli.clear()
def test_calcs(self):
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.assertAlmostEqual(self.cli.calc_similarity(d, d), 1, 6)
self.assertAlmostEqual(self.cli.calc_l2norm(d), sqrt(1*1 + 1*1+ 1*1 + 2*2), 6)
def test_clear(self):
self.cli.clear()
def test_save(self):
self.assertEqual(self.cli.save("recommender.save_test.model"), True)
def test_load(self):
model_name = "recommender.load_test.model"
self.cli.save(model_name)
self.assertEqual(self.cli.load(model_name), True)
def test_get_status(self):
self.cli.get_status()
def __init__(self, host=SERVER_IP, port=SERVER_PORT, name=NAME):
Recommender.__init__(self, host=host, port=port, name=name)
class RecommenderTest(unittest.TestCase):
def setUp(self):
self.config = {
"method": "inverted_index",
"converter": {
"string_filter_types": {},
"string_filter_rules": [],
"num_filter_types": {},
"num_filter_rules": [],
"string_types": {},
"string_rules": [{"key": "*", "type": "str", "sample_weight": "bin", "global_weight": "bin"}],
"num_types": {},
"num_rules": [{"key": "*", "type": "num"}]
},
"parameter": {}
}
TestUtil.write_file('config_recommender.json', json.dumps(self.config))
self.srv = TestUtil.fork_process('recommender', port, 'config_recommender.json')
try:
self.cli = Recommender(host, port, "name")
except:
TestUtil.kill_process(self.srv)
raise
def tearDown(self):
if self.cli:
self.cli.get_client().close()
TestUtil.kill_process(self.srv)
def test_get_client(self):
self.assertTrue(isinstance(self.cli.get_client(), msgpackrpc.client.Client))
def test_get_config(self):
config = self.cli.get_config()
self.assertEqual(json.dumps(json.loads(config), sort_keys=True), json.dumps(self.config, sort_keys=True))
def test_complete_row(self):
self.cli.clear_row("complete_row")
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.cli.update_row("complete_row", d)
d1 = self.cli.complete_row_from_id("complete_row")
d2 = self.cli.complete_row_from_datum(d)
def test_similar_row(self):
self.cli.clear_row("similar_row")
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.cli.update_row("similar_row", d)
s1 = self.cli.similar_row_from_id("similar_row", 10)
s2 = self.cli.similar_row_from_datum(d, 10)
def test_decode_row(self):
self.cli.clear_row("decode_row")
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.cli.update_row("decode_row", d)
decoded_row = self.cli.decode_row("decode_row")
self.assertEqual(json.dumps(d.string_values), json.dumps(decoded_row.string_values))
self.assertEqual(json.dumps(d.num_values), json.dumps(decoded_row.num_values))
def test_get_row(self):
self.cli.clear()
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.cli.update_row("get_row", d)
row_names = self.cli.get_all_rows()
self.assertEqual(row_names, ["get_row"])
def test_clear(self):
self.cli.clear()
def test_calcs(self):
d = Datum({"skey1": "val1", "skey2": "val2", "nkey1": 1.0, "nkey2": 2.0})
self.assertAlmostEqual(self.cli.calc_similarity(d, d), 1, 6)
self.assertAlmostEqual(self.cli.calc_l2norm(d), sqrt(1*1 + 1*1+ 1*1 + 2*2), 6)
def test_clear(self):
self.cli.clear()
def test_save(self):
self.assertEqual(len(self.cli.save("recommender.save_test.model")), 1)
def test_load(self):
model_name = "recommender.load_test.model"
self.cli.save(model_name)
self.assertEqual(self.cli.load(model_name), True)
def test_get_status(self):
self.cli.get_status()