def test_train_antinex_simple_success_retrain(self):
exchange = "webapp.train.requests"
routing_key = "webapp.train.requests"
queue = "webapp.train.requests"
max_models = 1
prc = AntiNexProcessor(max_models=max_models)
body = self.build_train_antinex_request()
self.assertEqual(body["ml_type"], "classification")
message = MockMessage(exchange=exchange,
routing_key=routing_key,
queue=queue)
self.assertEqual(message.state, "NOTRUN")
self.assertEqual(message.get_exchange(), exchange)
self.assertEqual(message.get_routing_key(), routing_key)
self.assertEqual(message.get_queue(), queue)
self.assertEqual(len(prc.models), 0)
prc.handle_messages(body=body, message=message)
self.assertEqual(message.state, "ACK")
self.assertEqual(len(prc.models), max_models)
self.assertEqual(len(prc.models), 1)
prc.handle_messages(body=body, message=message)
self.assertEqual(message.state, "ACK")
self.assertEqual(len(prc.models), max_models)
def test_train_antinex_simple_model_cleanup(self):
exchange = "webapp.train.requests"
routing_key = "webapp.train.requests"
queue = "webapp.train.requests"
max_models = 1
prc = AntiNexProcessor(max_models=max_models)
body = self.build_train_antinex_request()
self.assertEqual(body["ml_type"], "classification")
message = MockMessage(exchange=exchange,
routing_key=routing_key,
queue=queue)
self.assertEqual(message.state, "NOTRUN")
self.assertEqual(message.get_exchange(), exchange)
self.assertEqual(message.get_routing_key(), routing_key)
self.assertEqual(message.get_queue(), queue)
self.assertEqual(len(prc.models), 0)
prc.handle_messages(body=body, message=message)
self.assertEqual(message.state, "ACK")
self.assertEqual(len(prc.models), max_models)
# now try to train a new one and test the cleanup
body["label"] = "should-remove-the-first"
self.assertEqual(len(prc.models), 1)
prc.handle_messages(body=body, message=message)
self.assertEqual(message.state, "ACK")
self.assertEqual(len(prc.models), max_models)
for midx, model_name in enumerate(prc.models):
self.assertEqual(model_name, body["label"])
def test_scaler_first_time_predict_with_rows(self):
exchange = "webapp.predict.requests"
routing_key = "webapp.predict.requests"
queue = "webapp.predict.requests"
max_models = 1
prc = AntiNexProcessor(
max_models=max_models)
num_rows_at_bottom = 7
predict_rows_body = self.build_predict_rows_from_dataset(
num_rows_at_bottom=num_rows_at_bottom)
name_of_model = predict_rows_body["label"].lower().strip()
# make sure to remove the dataset arg to trigger
# the predict from just the list of dictionary rows
predict_rows_body.pop(
"dataset",
None)
self.assertEqual(
predict_rows_body["ml_type"],
"classification")
message = MockMessage(
exchange=exchange,
routing_key=routing_key,
queue=queue)
self.assertEqual(
message.state,
"NOTRUN")
self.assertEqual(
message.get_exchange(),
exchange)
self.assertEqual(
message.get_routing_key(),
routing_key)
self.assertEqual(
message.get_queue(),
queue)
self.assertEqual(
len(prc.models),
0)
prc.handle_messages(
body=predict_rows_body,
message=message)
self.assertEqual(
message.state,
"ACK")
self.assertEqual(
len(prc.models),
max_models)
model_data = prc.models[name_of_model]
print(len(model_data["data"]["sample_predictions"]))
self.assertTrue(
(len(model_data["data"]["sample_predictions"])
== num_rows_at_bottom))
num_rows_at_bottom = 4
predict_rows_body = self.build_predict_rows_from_dataset(
num_rows_at_bottom=num_rows_at_bottom)
# make sure to remove the dataset arg to trigger
# the predict from just the list of dictionary rows
predict_rows_body.pop(
"dataset",
None)
self.assertEqual(
len(prc.models),
1)
prc.handle_messages(
body=predict_rows_body,
message=message)
self.assertEqual(
message.state,
"ACK")
self.assertEqual(
len(prc.models),
max_models)
self.assertTrue(
name_of_model in prc.models)
model_data = prc.models[name_of_model]
self.assertTrue(
(len(model_data["data"]["sample_predictions"])
== num_rows_at_bottom))
