def test_valid(self):
"""Testing function valid."""
# Test with good data
data_dict = copy.deepcopy(self.data)
result = validate._CheckData(data_dict)
self.assertEqual(result.valid(), True)
# Test with bad data (base_type is non-numeric string)
data_dict = copy.deepcopy(self.data)
for agent_label, _ in data_dict['timeseries'].items():
data_dict['timeseries'][agent_label]['base_type'] = 'string'
break
result = validate._CheckData(data_dict)
self.assertEqual(result.valid(), False)
def test__data_keys_ok(self):
"""Testing function _data_keys_ok."""
# Test with good data
data_dict = copy.deepcopy(self.data)
result = validate._CheckData(data_dict)
self.assertEqual(result._data_keys_ok(), True)
# Test with bad data (no data keys)
data_dict = copy.deepcopy(self.data)
data_dict.pop('timefixed', None)
result = validate._CheckData(data_dict)
self.assertEqual(result._data_keys_ok(), False)
data_dict = copy.deepcopy(self.data)
data_dict.pop('timeseries', None)
result = validate._CheckData(data_dict)
self.assertEqual(result._data_keys_ok(), False)
def test__timeseries_data_ok(self):
"""Testing function _timeseries_data_ok."""
# Test with good data
data_dict = copy.deepcopy(self.data)
result = validate._CheckData(data_dict)
self.assertEqual(result._timeseries_data_ok(), True)
# Test with bad data (base_type is non-numeric string)
data_dict = copy.deepcopy(self.data)
for agent_label, _ in data_dict['timeseries'].items():
data_dict['timeseries'][agent_label]['base_type'] = 'string'
break
result = validate._CheckData(data_dict)
self.assertEqual(result._timeseries_data_ok(), False)
# Test with bad data ('data' value is non numeric)
data_dict = copy.deepcopy(self.data)
for agent_label, _ in data_dict['timeseries'].items():
data_dict['timeseries'][agent_label]['data'][0][1] = 'string'
break
result = validate._CheckData(data_dict)
self.assertEqual(result._timeseries_data_ok(), False)
# Test with good data (missing one time keys)
data_dict = copy.deepcopy(self.data)
data_dict.pop('timeseries', None)
result = validate._CheckData(data_dict)
self.assertEqual(result._timeseries_data_ok(), True)
data_dict = copy.deepcopy(self.data)
data_dict.pop('timefixed', None)
result = validate._CheckData(data_dict)
self.assertEqual(result._timeseries_data_ok(), True)
# Test with bad data (no timeseries key)
data_dict = copy.deepcopy(self.data)
data_dict.pop('timeseries', None)
data_dict.pop('timefixed', None)
result = validate._CheckData(data_dict)
self.assertEqual(result._timeseries_data_ok(), False)
# Test with bad data (no keys under agent_label)
data_dict = copy.deepcopy(self.data)
for _, sub_dict in data_dict['timeseries'].items():
sub_dict.pop('base_type', None)
result = validate._CheckData(sub_dict)
self.assertEqual(result._timeseries_data_ok(), False)
data_dict = copy.deepcopy(self.data)
for _, sub_dict in data_dict['timeseries'].items():
sub_dict.pop('data', None)
result = validate._CheckData(sub_dict)
self.assertEqual(result._timeseries_data_ok(), False)
def test__agent_label_keys_ok(self):
"""Testing function _agent_label_keys_ok."""
# Test with good data
data_dict = copy.deepcopy(self.data)
result = validate._CheckData(data_dict)
self.assertEqual(result._agent_label_keys_ok(), True)
# Test with good data (missing one time keys)
data_dict = copy.deepcopy(self.data)
data_dict.pop('timefixed', None)
result = validate._CheckData(data_dict)
self.assertEqual(result._agent_label_keys_ok(), True)
data_dict = copy.deepcopy(self.data)
data_dict.pop('timeseries', None)
result = validate._CheckData(data_dict)
self.assertEqual(result._agent_label_keys_ok(), True)
# Test with bad data (missing all time keys)
data_dict = copy.deepcopy(self.data)
data_dict.pop('timeseries', None)
data_dict.pop('timefixed', None)
result = validate._CheckData(data_dict)
self.assertEqual(result._agent_label_keys_ok(), False)
# Test with bad data (no keys under agent_label)
data_dict = copy.deepcopy(self.data)
for _, sub_dict in data_dict['timeseries'].items():
sub_dict.pop('base_type', None)
result = validate._CheckData(sub_dict)
self.assertEqual(result._agent_label_keys_ok(), False)
data_dict = copy.deepcopy(self.data)
for _, sub_dict in data_dict['timeseries'].items():
sub_dict.pop('description', None)
result = validate._CheckData(sub_dict)
self.assertEqual(result._agent_label_keys_ok(), False)
data_dict = copy.deepcopy(self.data)
for _, sub_dict in data_dict['timeseries'].items():
sub_dict.pop('data', None)
result = validate._CheckData(sub_dict)
self.assertEqual(result._agent_label_keys_ok(), False)
# Test with bad data (not enough keys under 'data')
data_dict = copy.deepcopy(self.data)
for agent_label, _ in data_dict['timeseries'].items():
data_dict['timeseries'][agent_label]['data'][0].remove(
data_dict['timeseries'][agent_label]['data'][0][-1])
break
result = validate._CheckData(sub_dict)
self.assertEqual(result._agent_label_keys_ok(), False)
def test___init__(self):
"""Testing function __init__."""
# Test with value that is not a dict
result = validate._CheckData('string')
self.assertEqual(result.valid(), False)
