def test_optimize(self):
"""
Test the launch of a simple OptimizeTask
"""
# Init
output = {
'uuid': 'optimize-task-uuid',
'type': 'optimize',
'status': 'PENDING'
}
self.presience_client.call = MagicMock(return_value=(200, output, {}))
dataset = Dataset(json={'dataset_id': 'my-dataset-id'},
prescience=self.presience_client)
# Test
optimize_task = dataset.optimize(budget=10,
scoring_metric=ScoringMetric.ACCURACY)
self.assertEqual('optimize-task-uuid', optimize_task.uuid())
self.assertEqual('optimize', optimize_task.type())
self.assertEqual(Status.PENDING, optimize_task.status())
self.presience_client.call.assert_called_with(
method='POST',
path='/ml/optimize/my-dataset-id',
content_type='application/json',
data={
'scoring_metric': 'accuracy',
'budget': 10
},
multipart=None,
query_parameters=None,
admin_call=False)
def test_get_evaluation_results(self):
"""
Test the access of evaluation results from a dataset
"""
# Init
output = {
'metadata': {
'page_number': 2,
'total_pages': 2,
'elements_on_page': 1,
'elements_total': 1,
'elements_type': 'EvaluationResult'
},
'content': [{
'uuid': 'azerty'
}]
}
self.presience_client.call = MagicMock(return_value=(200, output, {}))
dataset = Dataset(json={'dataset_id': 'my-dataset-id'},
prescience=self.presience_client)
dataset.evaluation_results(page=2)
self.presience_client.call.assert_called_with(
method='GET',
path='/evaluation-result',
query_parameters={
'dataset_id': 'my-dataset-id',
'page': 2
})
def test_delete_single_dataset(self):
"""
Test the deletion of a dataset
"""
self.presience_client.call = MagicMock(return_value=(200, {}, {}))
dataset = Dataset(json={'dataset_id': 'my-dataset-id'},
prescience=self.presience_client)
# Test 1
dataset.delete()
self.presience_client.call.assert_called_with(
method='DELETE',
path='/dataset/my-dataset-id',
expect_json_response=False)
def dataset(self) -> 'Dataset':
"""
Getter of the linked dataset for this task
:return: the dataset object
"""
from com.ovh.mls.prescience.core.bean.dataset import Dataset
return Dataset(json=self.initial_payload.get('dataset'), prescience=self.prescience)
def dataset(self, dataset_id: str):
"""
Get a single dataset from its ID
:param dataset_id: The dataset ID
:return: The dataset object
"""
_, source, _ = self.__get(path=f'/dataset/{dataset_id}')
from com.ovh.mls.prescience.core.bean.dataset import Dataset
return Dataset(json=source, prescience=self)
def test_create_dataset_mask(self):
"""
Test the creation of a dataset mask
"""
# Init
self.presience_client.call = MagicMock(return_value=(200, {}, {}))
dataset = Dataset(json={'dataset_id': 'my-dataset-id'},
prescience=self.presience_client)
dataset.create_mask(mask_id='dataset-mask',
selected_column=['col1', 'col2', 'label'])
self.presience_client.call.assert_called_with(
method='POST',
path='/dataset/mask/my-dataset-id',
query_parameters={'mask_id': 'dataset-mask'},
content_type='application/json',
data=['col1', 'col2', 'label'],
multipart=None,
admin_call=False)
def dataset(self):
"""
Getter of the linked dataset object
:return: the dataset object
"""
dataset_json = self.json_dict.get('dataset', None)
dataset = None
if dataset_json is not None:
dataset = Dataset(json=dataset_json, prescience=self.prescience)
return dataset
def create_mask(self, dataset_id: str, mask_id: str,
selected_column: list) -> 'Dataset':
"""
Create a Mask Dataset from a Dataset
:param dataset_id: The initial Dataset ID
:param mask_id: The new ID that we want to create for the Mask Dataset
:param selected_column: The subset of the initial Dataset that we want to keep for the Mask Dataset
:return: The new Mask Dataset
"""
query_parameters = {'mask_id': mask_id}
_, result, _ = self.__post(path=f'/dataset/mask/{dataset_id}',
data=selected_column,
query_parameters=query_parameters)
from com.ovh.mls.prescience.core.bean.dataset import Dataset
return Dataset(json=result, prescience=self)