def test_create_default(predictor_evaluation_workflow_dict: dict,
workflow: PredictorEvaluationWorkflow):
session = FakeSession()
session.set_response(predictor_evaluation_workflow_dict)
collection = PredictorEvaluationWorkflowCollection(project_id=uuid.uuid4(),
session=session)
default_workflow = collection.create_default(uuid.uuid4())
assert default_workflow.dump() == workflow.dump()
def test_create_default(valid_product_design_space_data,
valid_product_design_space):
# The instance field isn't renamed to config in objects returned from this route
# This renames the config key to instance to match the data we get from the API
data_with_instance = deepcopy(valid_product_design_space_data)
data_with_instance['instance'] = data_with_instance.pop('config')
session = FakeSession()
session.set_response(data_with_instance)
collection = DesignSpaceCollection(project_id=uuid.uuid4(),
session=session)
default_design_space = collection.create_default(uuid.uuid4())
assert default_design_space.dump() == valid_product_design_space.dump()
def test_check_update_none():
"""Test that check-for-updates makes the expected calls, parses output for no update."""
# Given
session = FakeSession()
session.set_response({"updatable": False})
pc = PredictorCollection(uuid.uuid4(), session)
predictor_id = uuid.uuid4()
# when
update_check = pc.check_for_update(predictor_id)
# then
assert update_check is None
expected_call = FakeCall(method='GET', path='/projects/{}/predictors/{}/check-for-update'.format(pc.project_id, predictor_id))
assert session.calls[0] == expected_call
def test_from_predictor_responses():
session = FakeSession()
col = 'smiles'
response_json = {
'responses': [ # shortened sample response
{
'category': 'Real',
'descriptor_key': 'khs.sNH3 KierHallSmarts for {}'.format(col),
'units': '',
'lower_bound': 0,
'upper_bound': 1000000000
},
{
'category': 'Real',
'descriptor_key': 'khs.dsN KierHallSmarts for {}'.format(col),
'units': '',
'lower_bound': 0,
'upper_bound': 1000000000
},
]
}
session.set_response(response_json)
descriptors = DescriptorMethods(uuid4(), session)
featurizer = MolecularStructureFeaturizer(
name="Molecule featurizer",
description="description",
descriptor=MolecularStructureDescriptor(col),
features=["all"],
excludes=["standard"])
results = descriptors.from_predictor_responses(
featurizer, [MolecularStructureDescriptor(col)])
assert results == [
RealDescriptor(
key=r['descriptor_key'],
lower_bound=r['lower_bound'],
upper_bound=r['upper_bound'],
) for r in response_json['responses']
]
assert session.last_call.path == '/projects/{}/material-descriptors/predictor-responses'\
.format(descriptors.project_id)
assert session.last_call.method == 'POST'
def test_returned_predictor(valid_graph_predictor_data):
"""Check that auto_configure works on the happy path."""
# Given
session = FakeSession()
# Setup a response that includes instance instead of config
response = deepcopy(valid_graph_predictor_data)
response["instance"] = response["config"]
del response["config"]
session.set_response(response)
pc = PredictorCollection(uuid.uuid4(), session)
# When
result = pc.auto_configure(GemTableDataSource(uuid.uuid4(), 0), "PLAIN")
# Then the response is parsed in a predictor
assert result.name == valid_graph_predictor_data["display_name"]
assert isinstance(result, GraphPredictor)
# including nested predictors
assert len(result.predictors) == 2
assert isinstance(result.predictors[0], uuid.UUID)
assert isinstance(result.predictors[1], DeprecatedExpressionPredictor)
def test_descriptors_from_data_source():
session = FakeSession()
col = 'smiles'
response_json = {
'descriptors': [ # shortened sample response
{
'category': 'Real',
'descriptor_key': 'khs.sNH3 KierHallSmarts for {}'.format(col),
'units': '',
'lower_bound': 0,
'upper_bound': 1000000000
},
{
'category': 'Real',
'descriptor_key': 'khs.dsN KierHallSmarts for {}'.format(col),
'units': '',
'lower_bound': 0,
'upper_bound': 1000000000
},
]
}
session.set_response(response_json)
descriptors = DescriptorMethods(uuid4(), session)
data_source = GemTableDataSource('43357a66-3644-4959-8115-77b2630aca45',
123)
results = descriptors.descriptors_from_data_source(data_source)
assert results == [
RealDescriptor(key=r['descriptor_key'],
lower_bound=r['lower_bound'],
upper_bound=r['upper_bound'],
units=r['units']) for r in response_json['descriptors']
]
assert session.last_call.path == '/projects/{}/material-descriptors/from-data-source'\
.format(descriptors.project_id)
assert session.last_call.method == 'POST'
def test_check_update_some():
"""Test the update check correctly builds a module."""
# given
session = FakeSession()
desc = RealDescriptor("spam", 0, 1, "kg")
response = {
"type": "AnalyticExpression",
"name": "foo",
"description": "bar",
"expression": "2 * x",
"output": RealDescriptor("spam", 0, 1, "kg").dump(),
"aliases": {}
}
session.set_response({"updatable": True, "update": response})
pc = PredictorCollection(uuid.uuid4(), session)
predictor_id = uuid.uuid4()
# when
update_check = pc.check_for_update(predictor_id)
# then
expected = ExpressionPredictor("foo", "bar", "2 * x", desc, {})
assert update_check.dump() == expected.dump()
assert update_check.uid == predictor_id