def configure_workflow(workflow, ret_list, connection_galaxy):
"""
Takes a workflow_uuid and associated data input map to return an expanded workflow
from core.models.workflow and workflow_data_input_map
"""
logger.debug("workflow.manager configure_workflow called")
curr_workflow = workflow
# gets galaxy internal id for specified workflow
workflow_galaxy_id = curr_workflow.internal_id
# gets dictionary version of workflow
workflow_dict = connection_galaxy.get_workflow_dict(workflow_galaxy_id)
# number of times to repeat workflow expansion
repeat_num = len(ret_list)
# creating base workflow to replicate input workflow
new_workflow = createBaseWorkflow((workflow_dict["name"]))
# checking to see what kind of workflow exists:
# does it have "annotation": "type=COMPACT", in the workflow annotation field
work_type = getStepOptions(workflow_dict["annotation"])
COMPACT_WORKFLOW = False
for k, v in work_type.iteritems():
if k.upper() == 'TYPE':
try:
if v[0].upper() == 'COMPACT':
COMPACT_WORKFLOW = True
except:
logger.exception("Malformed Workflow tag, cannot parse: %s" %
(work_type))
return
# if workflow is tagged w/ type=COMPACT tag,
if COMPACT_WORKFLOW:
logger.debug(
"workflow_manager.tasks.configure_workflow workflow processing: COMPACT"
)
new_workflow[
"steps"], history_download, analysis_node_connections = createStepsCompact(
ret_list, workflow_dict)
else:
logger.debug(
"workflow_manager.tasks.configure_workflow workflow processing: EXPANSION"
)
# Updating steps in imported workflow X number of times
new_workflow[
"steps"], history_download, analysis_node_connections = createStepsAnnot(
ret_list, workflow_dict)
return new_workflow, history_download, analysis_node_connections
def configure_workflow(workflow, ret_list, connection_galaxy):
"""
Takes a workflow_uuid and associated data input map to return an expanded workflow
from core.models.workflow and workflow_data_input_map
"""
logger.debug("workflow.manager configure_workflow called")
curr_workflow = workflow
# gets galaxy internal id for specified workflow
workflow_galaxy_id = curr_workflow.internal_id
# gets dictionary version of workflow
workflow_dict = connection_galaxy.get_workflow_dict(workflow_galaxy_id)
# number of times to repeat workflow expansion
repeat_num = len(ret_list)
# creating base workflow to replicate input workflow
new_workflow = createBaseWorkflow( (workflow_dict["name"]) )
# checking to see what kind of workflow exists:
# does it have "annotation": "type=COMPACT", in the workflow annotation field
work_type = getStepOptions(workflow_dict["annotation"])
COMPACT_WORKFLOW = False
for k,v in work_type.iteritems():
if k.upper() == 'TYPE':
try:
if v[0].upper() == 'COMPACT':
COMPACT_WORKFLOW = True
except:
logger.exception( "Malformed Workflow tag, cannot parse: %s" % (work_type) )
return
# if workflow is tagged w/ type=COMPACT tag,
if COMPACT_WORKFLOW:
logger.debug("workflow_manager.tasks.configure_workflow workflow processing: COMPACT")
new_workflow["steps"], history_download, analysis_node_connections = createStepsCompact(ret_list, workflow_dict)
else:
logger.debug("workflow_manager.tasks.configure_workflow workflow processing: EXPANSION")
# Updating steps in imported workflow X number of times
new_workflow["steps"], history_download, analysis_node_connections = createStepsAnnot(ret_list, workflow_dict);
return new_workflow, history_download, analysis_node_connections
def configure_workflow(workflow_dict, ret_list):
"""Takes a workflow and associated data input map
Returns an expanded workflow from core.models.workflow and
workflow_data_input_map
"""
logger.debug("workflow.manager configure_workflow called")
# creating base workflow to replicate input workflow
new_workflow = createBaseWorkflow(workflow_dict["name"])
# checking to see what kind of workflow exists:
# does it have "annotation": "type=COMPACT", in the workflow annotation
# field
work_type = getStepOptions(workflow_dict["annotation"])
COMPACT_WORKFLOW = False
for k, v in work_type.iteritems():
if k.upper() == 'TYPE':
try:
if v[0].upper() == 'COMPACT':
COMPACT_WORKFLOW = True
except:
logger.exception("Malformed workflow tag, cannot parse: %s",
work_type)
return
# if workflow is tagged w/ type=COMPACT tag,
if COMPACT_WORKFLOW:
logger.debug(
"workflow_manager.tasks.configure_workflow workflow processing: "
"COMPACT")
new_workflow["steps"], history_download, analysis_node_connections = \
createStepsCompact(ret_list, workflow_dict)
else:
logger.debug(
"workflow_manager.tasks.configure_workflow workflow processing: "
"EXPANSION")
# Updating steps in imported workflow X number of times
new_workflow["steps"], history_download, analysis_node_connections = \
createStepsAnnot(ret_list, workflow_dict)
return new_workflow, history_download, analysis_node_connections
