def test_2_broke_analisys(self):
'''
stop mindsdb while analyse dataset
'''
data = {
"integration_id": 'default_mariadb',
"name": TEST_DS,
"query": f"select * from test_data.{TEST_DATASET} limit 100;"
}
res = requests.put(f'{HTTP_API_ROOT}/datasources/{TEST_DS}', json=data)
assert res.status_code == 200
res = requests.get(f'{HTTP_API_ROOT}/datasources/{TEST_DS}/analyze')
assert res.status_code == 200
stop_mindsdb()
self.mdb, datastore = run_environment(
config,
apis=['mysql', 'http'],
override_integration_config={'default_mariadb': {
'publish': True
}},
mindsdb_database=MINDSDB_DATABASE,
clear_storage=False)
check_ds_exists(TEST_DS)
def test_4_wrong_prediction(self):
'''
close mindsdb while make prediction, then try run it again
'''
ioloop = asyncio.get_event_loop()
if ioloop.is_closed():
ioloop = asyncio.new_event_loop()
ioloop.run_in_executor(
None, lambda: requests.post(
f'{HTTP_API_ROOT}/predictors/{TEST_PREDICTOR}_2/predict',
json={'when': CONDITION}))
time.sleep(0.5)
stop_mindsdb()
ioloop.close()
self.mdb, datastore = run_environment(
config,
apis=['mysql', 'http'],
override_integration_config={'default_mariadb': {
'publish': True
}},
mindsdb_database=MINDSDB_DATABASE,
clear_storage=False)
res = requests.post(
f'{HTTP_API_ROOT}/predictors/{TEST_PREDICTOR}_2/predict',
json={'when': CONDITION})
assert res.status_code == 200
def test_2_restart_and_connect(self):
stop_mindsdb()
run_environment(apis=['mysql'],
override_config={
'integrations': {
'default_mariadb': {
'publish': False
}
}
})
config.update(json.loads(Path(CONFIG_PATH).read_text()))
def test_3_wrong_predictor(self):
'''
try create predictor with wrong parameters,
close mindsdb while model training
check mindsdb can start again
'''
check_predictor_not_exists(TEST_PREDICTOR)
data = {
'to_predict': list(TO_PREDICT.keys()),
'data_source_name': 'wrong ds'
}
res = requests.put(f'{HTTP_API_ROOT}/predictors/{TEST_PREDICTOR}',
json=data)
assert 'Can not find datasource' in res.json()['message']
check_predictor_not_exists(TEST_PREDICTOR)
data = {
'to_predict': list(TO_PREDICT.keys()),
'data_source_name': TEST_DS
}
res = requests.put(f'{HTTP_API_ROOT}/predictors/{TEST_PREDICTOR}',
json=data)
assert res.status_code == 200
stop_mindsdb()
self.mdb, datastore = run_environment(
config,
apis=['mysql', 'http'],
override_integration_config={'default_mariadb': {
'publish': True
}},
mindsdb_database=MINDSDB_DATABASE,
clear_storage=False)
# TODO add after this issue will be closed: https://github.com/mindsdb/mindsdb/issues/948
# check_predictor_not_exists(TEST_PREDICTOR)
data = {
'to_predict': list(TO_PREDICT.keys()),
'data_source_name': TEST_DS
}
res = requests.put(f'{HTTP_API_ROOT}/predictors/{TEST_PREDICTOR}_2',
json=data)
assert res.status_code == 200
wait_predictor_learn(f'{TEST_PREDICTOR}_2')
def test_3_restart_and_connect(self):
stop_mindsdb()
mdb, datastore = run_environment(
config,
apis=['mysql'],
override_integration_config={
'default_mariadb': {
'publish': True
}
},
mindsdb_database=MINDSDB_DATABASE,
clear_storage=False
)
self.mdb = mdb