def run_wf(debug, example_name):
logging.basicConfig(level=logging.DEBUG if debug else logging.INFO)
example_module = __import__(example_name)
wf = wfepy.Workflow()
wf.load_tasks(example_module)
wfepy.utils.render_graph(wf, os.path.join(os.path.dirname(__file__), example_name + '.gv'))
runner = wf.create_runner()
runner.run()
def setUp(self):
self.workflow = wfepy.Workflow()
self.workflow.load_tasks(__name__)
self.workflow.check_graph()
'state': [(name, istate.name) for name, istate in self.state],
})
def task_execute(self, task):
# Custom task execute code. We can add custom pre/post hooks, logging,
# pass extra variables to tasks (by defalt only context is passed to
# tasks) ... we can even prevent some task from executing and fake their
# results.
self.executed_tasks.add(task.name)
retval = task(self.context) # or `super().execute(task)`
if not retval and task.has_labels({'user'}):
logging.info('Waiting for user input in task %s.', task.name)
return retval
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
workflow = wf.Workflow()
workflow.load_tasks(__name__)
# Use custom runner instead of default one.
runner = Runner(workflow)
runner.run()
assert runner.executed_tasks == {'start', 'middle', 'end'}
import logging
import wfepy
import wfepy.utils
logging.basicConfig(level=logging.INFO)
# Import module with tasks.
import simple
# Create new workflow.
wf = wfepy.Workflow()
# Load tasks from module and add them to workflow.
wf.load_tasks(simple)
# Check if graph is OK, all tasks are defined, decorated correctly, ...
wf.check_graph()
# Render graph.
wfepy.utils.render_graph(wf, 'basic.gv')
# Create runner for workflow.
runner = wf.create_runner()
# Execute workflow.
runner.run()
# Check if workflow finished, no tasks are waiting.
while not runner.finished:
logging.info('Workflow is not finished, trying run it again...')
runner.run()
