def execute(self, request):
input_data = load_request(request)
required_parameters = ["project_id", "dataset_id", "pipeline_id"]
if set(required_parameters).issubset(input_data.keys()):
permissions = []
try:
project = Project.objects.get(id=int(input_data["project_id"]))
if not IsOwnerOfProject().has_object_permission(
request, self, project):
permissions.append("Unauthorized to access project.")
except Project.DoesNotExist:
project = None
try:
pipeline = Pipeline.objects.get(
id=int(input_data["pipeline_id"]))
if not IsOwnerOfPipeline().has_object_permission(
request, self, pipeline):
permissions.append("Unauthorized to access pipeline")
except Pipeline.DoesNotExist:
pipeline = None
try:
dataset = Dataset.objects.get(id=int(input_data["dataset_id"]))
if not IsOwnerOfDataset().has_object_permission(
request, self, dataset):
permissions.append("Unauthorized to access dataset")
except Dataset.DoesNotExist:
dataset = None
if len(permissions) > 0:
return Response(permissions,
status=status.HTTP_401_UNAUTHORIZED)
if project is None or dataset is None or pipeline is None:
message = []
if project is None:
message.append("No project found for id: {}".format(
input_data["project_id"]))
if dataset is None:
message.append("No dataset found for id: {}".format(
input_data["dataset_id"]))
if pipeline is None:
message.append("No pipeline found for id: {}".format(
input_data["pipeline_id"]))
return Response(", ".join(message),
status=status.HTTP_400_BAD_REQUEST)
try:
DaskTasks.setup_task(project_id=project.id,
dataset_id=dataset.id,
pipeline_id=pipeline.id)
response = "Successfully executed pipeline"
except Exception as ex:
response = "Error occured attempting to execute pipeline. Message: {}".format(
ex)
return Response(response, status=status.HTTP_200_OK)
else:
return Response(
"Missing required parameters in POST request. Required parameters: {}"
.format(", ".join(required_parameters)),
status.HTTP_400_BAD_REQUEST)
def refit_model(self, request):
input_data = load_request(request)
required_parameters = ["project_id", "model_id", "predictive_models"]
if set(required_parameters).issubset(input_data.keys()):
permissions = []
try:
project = Project.objects.get(id=int(input_data["project_id"]))
if not IsOwnerOfProject().has_object_permission(
request, self, project):
permissions.append("Unauthorized to access project.")
except Project.DoesNotExist:
project = None
try:
model = Model.objects.get(id=int(input_data["model_id"]))
if not IsOwnerOfModel().has_object_permission(
request, self, model):
permissions.append("Unauthorized to access pipeline")
except Model.DoesNotExist:
model = None
if len(permissions) > 0:
return Response(permissions,
status=status.HTTP_401_UNAUTHORIZED)
if model is None or project is None:
message = []
if project is None:
message.append("No project found for id: {}".format(
input_data["project_id"]))
if model is None:
message.append("No model found for id: {}".format(
input_data["model_id"]))
return Response(", ".join(message),
status=status.HTTP_400_BAD_REQUEST)
p_models = {}
for p in json.loads(input_data["predictive_models"]):
p_models[p[0]] = int(p[1])
m = Metadata(model, json.dumps({"predictive_models": p_models}))
meta = m.set_metadata("ModelMetadata")
response = {}
DaskTasks.refit_task(project.id, model.id, p_models)
response["project_id"] = project.id
response["pipeline_id"] = model.pipeline.id
response["model_id"] = model.id
response["dataset_id"] = project.dataset
response["model_metadata"] = meta
response[
"status"] = "Initiated refit for specified models for prediction"
return Response(response, status=status.HTTP_200_OK)
data = "Missing required parameters: {}".format(
", ".join(required_parameters))
response_status = status.HTTP_200_OK
return Response(data, status=response_status)
def execute(self, request):
input_data = request.data.dict()
required_parameters = ["workflow_id", "dataset_id", "model_id"]
if set(required_parameters).issubset(input_data.keys()):
try:
workflow = Workflow.objects.get(id=int(input_data["workflow_id"]))
except ObjectDoesNotExist:
workflow = None
try:
amodel = AnalyticalModel.objects.get(id=int(input_data["model_id"]))
except ObjectDoesNotExist:
amodel = None
try:
dataset = Dataset.objects.get(id=int(input_data["dataset_id"]))
except ObjectDoesNotExist:
dataset = None
if workflow is None or dataset is None or amodel is None:
message = []
if workflow is None:
message.append("No workflow found for id: {}".format(input_data["workflow_id"]))
if dataset is None:
message.append("No dataset found for id: {}".format(input_data["dataset_id"]))
if amodel is None:
message.append("No analytical model found for id: {}".format(input_data["model_id"]))
return Response(", ".join(message), status=status.HTTP_400_BAD_REQUEST)
elif IsOwnerOfLocationChild().has_object_permission(request, self, workflow):
try:
DaskTasks.setup_task(dataset_id=dataset.id, amodel_id=amodel.id)
response = "Successfully executed analytical model"
except Exception as ex:
response = "Error occured attempting to execute analytical model. Message: {}".format(ex)
return Response(response, status=status.HTTP_200_OK)
else:
return Response(status=status.HTTP_401_UNAUTHORIZED)
else:
return Response(
"Missing required parameters in POST request. Required parameters: {}".format(", ".join(required_parameters)),
status.HTTP_400_BAD_REQUEST
)
def evaluate(self, request):
"""
:param request:
:return:
"""
input_data = load_request(request)
required_parameters = ["project_id", "model_id"]
if set(required_parameters).issubset(input_data.keys()):
permissions = []
try:
project = Project.objects.get(id=int(input_data["project_id"]))
if not IsOwnerOfProject().has_object_permission(
request, self, project):
permissions.append("Unauthorized to access project.")
except Project.DoesNotExist:
project = None
try:
model = Model.objects.get(id=int(input_data["model_id"]))
if not IsOwnerOfModel().has_object_permission(
request, self, model):
permissions.append("Unauthorized to access pipeline")
except Model.DoesNotExist:
model = None
if len(permissions) > 0:
return Response(permissions,
status=status.HTTP_401_UNAUTHORIZED)
if model is None or project is None:
message = []
if project is None:
message.append("No project found for id: {}".format(
input_data["project_id"]))
if model is None:
message.append("No model found for id: {}".format(
input_data["model_id"]))
return Response(", ".join(message),
status=status.HTTP_400_BAD_REQUEST)
flag = input_data["flag"] if "flag" in input_data.keys() else None
response = {}
results = DaskTasks.evaluate(project.id, model.id, flag)
response["project_id"] = project.id
response["pipeline_id"] = model.pipeline.id
response["model_id"] = model.id
response["dataset_id"] = project.dataset
response["results"] = results
return Response(response, status=status.HTTP_200_OK)
data = "Missing required parameters: {}".format(
", ".join(required_parameters))
response_status = status.HTTP_200_OK
return Response(data, status=response_status)
def data(self, request):
inputs = request.data.dict()
required_parameters = ["workflow_id", "model_id"]
if set(required_parameters).issubset(inputs.keys()):
try:
workflow = Workflow.objects.get(id=int(inputs["workflow_id"]))
except ObjectDoesNotExist:
workflow = None
try:
amodel = AnalyticalModel.objects.get(id=int(inputs["model_id"]))
except ObjectDoesNotExist:
amodel = None
if workflow is None or amodel is None:
message = []
message = message if workflow else message.append("No workflow found for id: {}".format(inputs["workflow_id"]))
message = message if amodel else message.append("No analytical model found for id: {}".format(inputs["amodel_id"]))
return Response(",".join(message), status=status.HTTP_400_BAD_REQUEST)
elif IsOwnerOfLocationChild().has_object_permission(request, self, workflow):
response = {}
meta = Metadata(parent=amodel)
metadata = meta.get_metadata("ModelMetadata", ['status', 'stage', 'message'])
response["metadata"] = metadata
completed = False
if "stage" in metadata.keys():
i = metadata["stage"].split("/")
if int(i[0]) == int(i[1]):
completed = True
if completed:
if amodel.model:
data = None
if "data" in inputs.keys():
data = pd.read_csv(StringIO(inputs["data"]))
response["data"] = DaskTasks.make_prediction(amodel.id, data)
response["dataset_id"] = amodel.dataset
response["analytical_model_id"] = amodel.id
response["workflow_id"] = workflow.id
return Response(response, status=status.HTTP_200_OK)
data = "Missing required parameters: {}".format(", ".join(required_parameters))
response_status = status.HTTP_200_OK
return Response(data, status=response_status)