Closed jeff1evesque closed 8 years ago
Our error traceback has been reduced to the following:
vagrant@vagrant-ubuntu-trusty-64:/vagrant/test$ py.test
============================= test session starts ==============================
platform linux2 -- Python 2.7.6, pytest-2.9.1, py-1.4.31, pluggy-0.3.1
rootdir: /vagrant/test, inifile: pytest.ini
collected 4 items
programmatic_interface/pytest_session.py ..FF
=================================== FAILURES ===================================
_____________________________ check_model_generate _____________________________
def check_model_generate():
"""@check_model_generate
This method tests the 'model_generate' session.
"""
> assert requests.post(
endpoint_url,
headers=headers,
data=get_sample_json('svm-model-generate.json')
)
E assert <Response [500]>
E + where <Response [500]> = <function post at 0x7f3e2b168de8>('http://l
ocalhost:5000/load-data/', headers={'Content-Type': 'application/json'}, data='{
"properties": {"model_type": "classification", "sv_kernel_type": "rbf", "session
_id": "1", "session_type": "model_generate"}}')
E + where <function post at 0x7f3e2b168de8> = requests.post
E + and '{"properties": {"model_type": "classification", "sv_kernel_
type": "rbf", "session_id": "1", "session_type": "model_generate"}}' = get_sampl
e_json('svm-model-generate.json')
programmatic_interface/pytest_session.py:97: AssertionError
_____________________________ check_model_predict ______________________________
def check_model_predict():
"""@check_model_predict
This method tests the 'model_predict' session.
"""
> assert requests.post(
endpoint_url,
headers=headers,
data=get_sample_json('svm-model-predict.json')
)
E assert <Response [500]>
E + where <Response [500]> = <function post at 0x7f3e2b168de8>('http://l
ocalhost:5000/load-data/', headers={'Content-Type': 'application/json'}, data='{
"properties": {"model_id": "1", "prediction_input[]": ["22.22", "96.24", "338",
"72.55", "0.001", "28", "0.678"], "session_type": "model_predict"}}')
E + where <function post at 0x7f3e2b168de8> = requests.post
E + and '{"properties": {"model_id": "1", "prediction_input[]": ["22
.22", "96.24", "338", "72.55", "0.001", "28", "0.678"], "session_type": "model_p
redict"}}' = get_sample_json('svm-model-predict.json')
programmatic_interface/pytest_session.py:111: AssertionError
====================== 2 failed, 2 passed in 1.59 seconds ======================
Currently, no feature_count
is being stored into the tbl_feature_count
sql table, during a programmatic implementation for the new dataset, or append dataset session. Several possibilities include:
We need to resolve the following error traceback, generated via our unit tests from
pytest_session.py
: