def grab_workflows(instance=None, connection_galaxy=None):
# Delete old references to workflows
Workflow.objects.all().delete()
# checks to see if an existing galaxy connection, otherwise create a connection
if (connection_galaxy is None):
print("instance is none")
#get connection
instance = Instance.objects.all()[0]
connection_galaxy = instance.get_galaxy_connection()
#get all your workflows
workflows = connection_galaxy.get_complete_workflows()
#for each workflow, create a core Workflow object and its associated WorkflowDataInput objects
for workflow in workflows:
workflow_dict = {
'name': workflow.name,
'internal_id': workflow.identifier
#'visibility': 2 #give public visibility for now
}
w = Workflow(**workflow_dict)
try:
w.save()
inputs = workflow.inputs
for input in inputs:
input_dict = {
'name': input.name,
'internal_id': input.identifier
}
i = WorkflowDataInput(**input_dict)
i.save()
w.data_inputs.add(i)
except:
connection.rollback()
def grab_workflows(instance=None, connection_galaxy=None):
# Delete old references to workflows
Workflow.objects.all().delete()
# checks to see if an existing galaxy connection, otherwise create a connection
if (connection_galaxy is None):
print ("instance is none")
#get connection
instance = Instance.objects.all()[0]
connection_galaxy = instance.get_galaxy_connection()
#get all your workflows
workflows = connection_galaxy.get_complete_workflows()
#for each workflow, create a core Workflow object and its associated WorkflowDataInput objects
for workflow in workflows:
workflow_dict = {
'name': workflow.name,
'internal_id': workflow.identifier
#'visibility': 2 #give public visibility for now
}
w = Workflow(**workflow_dict)
try:
w.save()
inputs = workflow.inputs
for input in inputs:
input_dict = {
'name': input.name,
'internal_id': input.identifier
}
i = WorkflowDataInput(**input_dict)
i.save()
w.data_inputs.add(i)
except:
connection.rollback()
def import_workflow(workflow, workflow_engine, workflow_dictionary):
issues = []
has_step_issues = False
has_input_issues = False
has_annotation_issues = False
workflow_annotation = get_workflow_annotation(workflow_dictionary)
if workflow_annotation is None:
issues.append("Workflow annotation not found.")
return issues
workflow_type = get_workflow_type(workflow_annotation)
if workflow_type is None:
issues.append("Workflow type not found.")
return issues
# check workflow inputs for correct annotations
workflow_input_issues = check_workflow_inputs(workflow_dictionary)
if len(workflow_input_issues) > 0:
has_input_issues = True
issues = issues + workflow_input_issues
# check workflow steps for correct annotations and skip import if problems are detected
workflow_step_issues = check_steps(workflow_dictionary)
if workflow_step_issues is None: # no error in parsing but no outputs defined
issues.append("Workflow does not declare outputs.")
has_step_issues = True
else:
if len(workflow_step_issues) > 0:
has_step_issues = True
issues = issues + workflow_step_issues
# skip import if workflow has incorrect input annotations or step annotation
if has_step_issues or has_input_issues:
return issues
# import workflow
if workflow_type is not None: # if workflow is meant for refinery
workflow_object = Workflow.objects.create(
name=workflow.name,
internal_id=workflow.identifier,
workflow_engine=workflow_engine,
is_active=True,
type=workflow_type,
graph=json.dumps(workflow_dictionary))
workflow_object.set_manager_group(workflow_engine.get_manager_group())
workflow_object.share(
workflow_engine.get_manager_group().get_managed_group())
inputs = workflow.inputs
# Adding workflowdatainputs i.e. inputs from workflow into database models
for input in inputs:
input_dict = {'name': input.name, 'internal_id': input.identifier}
i = WorkflowDataInput(**input_dict)
i.save()
workflow_object.data_inputs.add(i)
# if workflow has only 1 input, input a default input relationship type
if (len(inputs) == 1):
opt_single = {'category': TYPE_1_1, 'set1': input.name}
temp_relationship = WorkflowInputRelationships(**opt_single)
temp_relationship.save()
workflow_object.input_relationships.add(temp_relationship)
# check to input NodeRelationshipType
# noderelationship types defined for workflows with greater than 1 input
# refinery_relationship=[{"category":"N-1", "set1":"input_file"}]
workflow_relationships = get_input_relationships(workflow_annotation)
if workflow_relationships is not None:
if (len(inputs) > 1):
for opt_r in workflow_relationships:
try:
temp_relationship = WorkflowInputRelationships(**opt_r)
temp_relationship.save()
workflow_object.input_relationships.add(
temp_relationship)
except KeyError, e:
logger.error()
issues.append("Input relationship option error: %s" %
e)
def import_workflow(workflow, workflow_engine, workflow_dictionary):
issues = []
has_step_issues = False
has_input_issues = False
workflow_annotation = get_workflow_annotation(workflow_dictionary)
if workflow_annotation is None:
issues.append("Workflow annotation not found.")
return issues
workflow_type = get_workflow_type(workflow_annotation)
if workflow_type is None:
issues.append("Workflow type not found.")
return issues
# check workflow inputs for correct annotations
workflow_input_issues = check_workflow_inputs(workflow_dictionary)
if len(workflow_input_issues) > 0:
has_input_issues = True
issues = issues + workflow_input_issues
# check workflow steps for correct annotations and skip import if problems
# are detected
workflow_step_issues = check_steps(workflow_dictionary)
if workflow_step_issues is None:
# no error in parsing but no outputs defined
issues.append("Workflow does not declare outputs.")
has_step_issues = True
else:
if len(workflow_step_issues) > 0:
has_step_issues = True
issues = issues + workflow_step_issues
# skip import if workflow has incorrect input annotations or step
# annotation
if has_step_issues or has_input_issues:
return issues
# import workflow
if workflow_type is not None: # if workflow is meant for refinery
workflow_object = Workflow.objects.create(
name=workflow.name, internal_id=workflow.identifier,
workflow_engine=workflow_engine, is_active=True,
type=workflow_type, graph=json.dumps(workflow_dictionary))
workflow_object.set_manager_group(workflow_engine.get_manager_group())
workflow_object.share(
workflow_engine.get_manager_group().get_managed_group())
inputs = workflow.inputs
# Adding workflowdatainputs i.e. inputs from workflow into database
# models
for input in inputs:
input_dict = {
'name': input.name,
'internal_id': input.identifier
}
i = WorkflowDataInput(**input_dict)
i.save()
workflow_object.data_inputs.add(i)
# if workflow has only 1 input, input a default input relationship
# type
if len(inputs) == 1:
opt_single = {
'category': TYPE_1_1,
'set1': input.name
}
temp_relationship = WorkflowInputRelationships(**opt_single)
temp_relationship.save()
workflow_object.input_relationships.add(temp_relationship)
# check to input NodeRelationshipType
# noderelationship types defined for workflows with greater than 1
# input
# refinery_relationship=[{"category":"N-1", "set1":"input_file"}]
workflow_relationships = get_input_relationships(workflow_annotation)
if workflow_relationships is not None:
if len(inputs) > 1:
for opt_r in workflow_relationships:
try:
temp_relationship = WorkflowInputRelationships(**opt_r)
temp_relationship.save()
workflow_object.input_relationships.add(
temp_relationship)
except KeyError as e:
logger.error(e)
issues.append(
"Input relationship option error: %s" % e)
return issues
