def execute(self, tool, trans, incoming=None, set_output_hid=False, overwrite=True, history=None, job_params=None, execution_cache=None, collection_info=None, job_callback=None, **kwargs):
incoming = incoming or {}
trans.check_user_activation()
if execution_cache is None:
execution_cache = ToolExecutionCache(trans)
current_user_roles = execution_cache.current_user_roles
history, inp_data, inp_dataset_collections, preserved_tags, all_permissions = self._collect_inputs(tool, trans, incoming, history, current_user_roles, collection_info)
# Build name for output datasets based on tool name and input names
on_text = self._get_on_text(inp_data)
# wrapped params are used by change_format action and by output.label; only perform this wrapping once, as needed
wrapped_params = self._wrapped_params(trans, tool, incoming)
out_data = {}
input_collections = {k: v[0][0] for k, v in inp_dataset_collections.items()}
output_collections = OutputCollections(
trans,
history,
tool=tool,
tool_action=self,
input_collections=input_collections,
dataset_collection_elements=kwargs.get("dataset_collection_elements", None),
on_text=on_text,
incoming=incoming,
params=wrapped_params.params,
job_params=job_params,
tags=preserved_tags,
)
#
# Create job.
#
job, galaxy_session = self._new_job_for_session(trans, tool, history)
self._produce_outputs(trans, tool, out_data, output_collections, incoming=incoming, history=history, tags=preserved_tags)
self._record_inputs(trans, tool, job, incoming, inp_data, inp_dataset_collections)
self._record_outputs(job, out_data, output_collections)
if job_callback:
job_callback(job)
job.state = job.states.OK
trans.sa_session.add(job)
# Queue the job for execution
# trans.app.job_manager.job_queue.put( job.id, tool.id )
# trans.log_event( "Added database job action to the job queue, id: %s" % str(job.id), tool_id=job.tool_id )
log.info("Calling produce_outputs, tool is %s" % tool)
return job, out_data, history
def execute( self, tool, trans, incoming={}, set_output_hid=False, overwrite=True, history=None, job_params=None, mapping_over_collection=False, execution_cache=None, **kwargs ):
if execution_cache is None:
execution_cache = ToolExecutionCache(trans)
current_user_roles = execution_cache.current_user_roles
history, inp_data, inp_dataset_collections = self._collect_inputs(tool, trans, incoming, history, current_user_roles)
# Build name for output datasets based on tool name and input names
on_text = self._get_on_text( inp_data )
# wrapped params are used by change_format action and by output.label; only perform this wrapping once, as needed
wrapped_params = self._wrapped_params( trans, tool, incoming )
out_data = odict()
input_collections = dict( [ (k, v[0][0]) for k, v in inp_dataset_collections.iteritems() ] )
output_collections = OutputCollections(
trans,
history,
tool=tool,
tool_action=self,
input_collections=input_collections,
mapping_over_collection=mapping_over_collection,
on_text=on_text,
incoming=incoming,
params=wrapped_params.params,
job_params=job_params,
)
#
# Create job.
#
job, galaxy_session = self._new_job_for_session( trans, tool, history )
self._produce_outputs( trans, tool, out_data, output_collections, incoming=incoming, history=history )
self._record_inputs( trans, tool, job, incoming, inp_data, inp_dataset_collections, current_user_roles )
self._record_outputs( job, out_data, output_collections )
job.state = job.states.OK
trans.sa_session.add( job )
trans.sa_session.flush() # ensure job.id are available
# Queue the job for execution
# trans.app.job_queue.put( job.id, tool.id )
# trans.log_event( "Added database job action to the job queue, id: %s" % str(job.id), tool_id=job.tool_id )
log.info("Calling produce_outputs, tool is %s" % tool)
return job, out_data