uncomment invoke_wf

run_workflow_phaeoexplorer.py

@@ -987,12 +987,13 @@ if __name__ == "__main__":
 
     args = parser.parse_args()
 
+    bioblend_logger = logging.getLogger("bioblend")
     if args.verbose:
         logging.basicConfig(level=logging.DEBUG)
+        bioblend_logger.setLevel(logging.DEBUG)
     else:
         logging.basicConfig(level=logging.INFO)
-    logging.getLogger("urllib3").setLevel(logging.INFO)
-    logging.getLogger("bioblend").setLevel(logging.INFO)
+        bioblend_logger.setLevel(logging.INFO)
 
     # Parsing the config file if provided, using the default config otherwise
     if not args.config:
@@ -1000,6 +1001,12 @@ if __name__ == "__main__":
     else:
         args.config = os.path.abspath(args.config)
 
+    if args.config:
+        config_file = os.path.abspath(args.config)
+    else:
+        config_file = os.path.join(os.path.dirname(os.path.realpath(sys.argv[0])), constants.DEFAULT_CONFIG)
+    config = utilities.parse_config(config_file)
+
     if not args.main_directory:
         args.main_directory = os.getcwd()
     else:
@@ -1190,7 +1197,7 @@ if __name__ == "__main__":
                         logging.warning("Error finding workflow %s" % workflow_name)
 
                     # Finally, invoke the workflow alogn with its datamap, parameters and the history in which to invoke it
-                    # instance.workflows.invoke_workflow(workflow_id=workflow_id, history_id=history_id, params=workflow_parameters, inputs=datamap, allow_tool_state_corrections=True)
+                    instance.workflows.invoke_workflow(workflow_id=workflow_id, history_id=history_id, params=workflow_parameters, inputs=datamap, allow_tool_state_corrections=True)
 
                     logging.info("Successfully imported and invoked workflow {0}, check the galaxy instance ({1}) for the jobs state".format(workflow_name, instance_url))
 
@@ -1426,7 +1433,7 @@ if __name__ == "__main__":
                         logging.warning("Error finding workflow %s" % workflow_name)
 
                     # Finally, invoke the workflow alogn with its datamap, parameters and the history in which to invoke it
-                    # instance.workflows.invoke_workflow(workflow_id=workflow_id, history_id=history_id, params=workflow_parameters, inputs=datamap, allow_tool_state_corrections=True)
+                    instance.workflows.invoke_workflow(workflow_id=workflow_id, history_id=history_id, params=workflow_parameters, inputs=datamap, allow_tool_state_corrections=True)
 
                     logging.info("Successfully imported and invoked workflow {0}, check the galaxy instance ({1}) for the jobs state".format(workflow_name, instance_url))
 
@@ -1541,7 +1548,7 @@ if __name__ == "__main__":
                     logging.warning("Error finding workflow %s" % workflow_name)
 
                 # Finally, invoke the workflow alogn with its datamap, parameters and the history in which to invoke it
-                # instance.workflows.invoke_workflow(workflow_id=workflow_id, history_id=history_id, params=workflow_parameters, inputs=datamap, allow_tool_state_corrections=True)
+                instance.workflows.invoke_workflow(workflow_id=workflow_id, history_id=history_id, params=workflow_parameters, inputs=datamap, allow_tool_state_corrections=True)
 
                 logging.info("Successfully imported and invoked workflow {0}, check the galaxy instance ({1}) for the jobs state".format(workflow_name, instance_url))
 
@@ -1695,7 +1702,7 @@ if __name__ == "__main__":
                     logging.warning("Error finding workflow %s" % workflow_name)
 
                 # Finally, invoke the workflow alogn with its datamap, parameters and the history in which to invoke it
-                # instance.workflows.invoke_workflow(workflow_id=workflow_id, history_id=history_id, params=workflow_parameters, inputs=datamap, allow_tool_state_corrections=True)
+                instance.workflows.invoke_workflow(workflow_id=workflow_id, history_id=history_id, params=workflow_parameters, inputs=datamap, allow_tool_state_corrections=True)
 
                 logging.info("Successfully imported and invoked workflow {0}, check the galaxy instance ({1}) for the jobs state".format(workflow_name, instance_url))