Python client for Conductor

Python clinet for Conductor provides two sets of functions:

1. Workflow management APIs (start, terminate, get workflow status etc.)
2. Worker execution framework

Install

pip install conductor

Using Workflow Management API

Python class WorkflowClient provides client API calls to the conductor server to start manage the workflows.

Example

import sys
from conductor import conductor
import json

def getStatus(workflowId):
	
	workflowClient = conductor.WorkflowClient('http://localhost:8080/api')
	
	workflow_json = workflowClient.getWorkflow(workflowId)
	print json.dumps(workflow_json, indent=True, separators=(',', ': '))
	
	return workflow_json
	

Task Worker Execution

Task worker execution APIs facilitates execution of a task worker using python client. The API provides necessary mechanism to poll for task work at regular interval and executing the python worker in a separate threads.

Example

The following python script demonstrates workers for the kitchensink workflow.

from conductor.ConductorWorker import ConductorWorker

def execute(task):
	return {'status': 'COMPLETED', 'output': {'mod': 5, 'taskToExecute': 'task_1', 'oddEven': 0}}

def execute4(task):
	forkTasks = [{"name": "task_1", "taskReferenceName": "task_1_1", "type": "SIMPLE"},{"name": "sub_workflow_4", "taskReferenceName": "wf_dyn", "type": "SUB_WORKFLOW", "subWorkflowParam": {"name": "sub_flow_1"}}];
	input = {'task_1_1': {}, 'wf_dyn': {}}
	return {'status': 'COMPLETED', 'output': {'mod': 5, 'taskToExecute': 'task_1', 'oddEven': 0, 'dynamicTasks': forkTasks, 'inputs': input}}

def main():
	print 'Hello World'
	cc = ConductorWorker('http://localhost:8080/api', 1, 0.1)
	for x in range(1, 30):
		if(x == 4):
			cc.start('task_{0}'.format(x), execute4, False)
		else:
			cc.start('task_{0}'.format(x), execute, False)
	cc.start('task_30', execute, True)

if __name__ == '__main__':
    main()