def process_finished_workflow_jobs(self, workflow_jobs):
result = []
for workflow_job in workflow_jobs:
dag = WorkflowDAG(workflow_job)
if workflow_job.cancel_flag:
logger.debug(
'Canceling spawned jobs of %s due to cancel flag.',
workflow_job.log_format)
cancel_finished = dag.cancel_node_jobs()
if cancel_finished:
logger.info(
'Marking %s as canceled, all spawned jobs have concluded.',
workflow_job.log_format)
workflow_job.status = 'canceled'
workflow_job.save()
connection.on_commit(
lambda: workflow_job.websocket_emit_status(workflow_job
.status))
else:
is_done, has_failed = dag.is_workflow_done()
if not is_done:
continue
logger.info('Marking %s as %s.', workflow_job.log_format,
'failed' if has_failed else 'successful')
result.append(workflow_job.id)
workflow_job.status = 'failed' if has_failed else 'successful'
workflow_job.save()
connection.on_commit(
lambda: workflow_job.websocket_emit_status(workflow_job.
status))
return result
def process_finished_workflow_jobs(self, workflow_jobs):
result = []
for workflow_job in workflow_jobs:
dag = WorkflowDAG(workflow_job)
if workflow_job.cancel_flag:
logger.debug(
'Canceling spawned jobs of %s due to cancel flag.',
workflow_job.log_format)
cancel_finished = dag.cancel_node_jobs()
if cancel_finished:
logger.info(
'Marking %s as canceled, all spawned jobs have concluded.',
workflow_job.log_format)
workflow_job.status = 'canceled'
workflow_job.start_args = '' # blank field to remove encrypted passwords
workflow_job.save(update_fields=['status', 'start_args'])
workflow_job.websocket_emit_status(workflow_job.status)
else:
is_done, has_failed = dag.is_workflow_done()
if not is_done:
continue
logger.info('Marking %s as %s.', workflow_job.log_format,
'failed' if has_failed else 'successful')
result.append(workflow_job.id)
new_status = 'failed' if has_failed else 'successful'
logger.debug(
six.text_type("Transitioning {} to {} status.").format(
workflow_job.log_format, new_status))
workflow_job.status = new_status
workflow_job.start_args = '' # blank field to remove encrypted passwords
workflow_job.save(update_fields=['status', 'start_args'])
workflow_job.websocket_emit_status(workflow_job.status)
return result
def test_workflow_dnr_because_parent(self, workflow_job_fn):
wfj, nodes = workflow_job_fn(states=['successful', None, None, None, None, None,])
dag = WorkflowDAG(workflow_job=wfj)
workflow_nodes = dag.mark_dnr_nodes()
assert 2 == len(workflow_nodes)
assert nodes[3] in workflow_nodes
assert nodes[4] in workflow_nodes
def test_workflow_fails_leaf(self):
wfj = self.workflow_job(
states=['successful', 'successful', 'failed', None, None])
dag = WorkflowDAG(workflow_job=wfj)
is_done, has_failed = dag.is_workflow_done()
self.assertTrue(is_done)
self.assertTrue(has_failed)
def spawn_workflow_graph_jobs(self, workflow_jobs):
for workflow_job in workflow_jobs:
dag = WorkflowDAG(workflow_job)
spawn_nodes = dag.bfs_nodes_to_run()
for spawn_node in spawn_nodes:
if spawn_node.unified_job_template is None:
continue
kv = spawn_node.get_job_kwargs()
job = spawn_node.unified_job_template.create_unified_job(**kv)
spawn_node.job = job
spawn_node.save()
if job._resources_sufficient_for_launch():
can_start = job.signal_start()
if not can_start:
job.job_explanation = _(
"Job spawned from workflow could not start because it "
"was not in the right state or required manual credentials"
)
else:
can_start = False
job.job_explanation = _(
"Job spawned from workflow could not start because it "
"was missing a related resource such as project or inventory"
)
if not can_start:
job.status = 'failed'
job.save(update_fields=['status', 'job_explanation'])
connection.on_commit(
lambda: job.websocket_emit_status('failed'))
def spawn_workflow_graph_jobs(self, workflow_jobs):
for workflow_job in workflow_jobs:
if workflow_job.cancel_flag:
logger.debug('Not spawning jobs for %s because it is pending cancelation.', workflow_job.log_format)
continue
dag = WorkflowDAG(workflow_job)
spawn_nodes = dag.bfs_nodes_to_run()
if spawn_nodes:
logger.debug('Spawning jobs for %s', workflow_job.log_format)
else:
logger.debug('No nodes to spawn for %s', workflow_job.log_format)
for spawn_node in spawn_nodes:
if spawn_node.unified_job_template is None:
continue
kv = spawn_node.get_job_kwargs()
job = spawn_node.unified_job_template.create_unified_job(**kv)
spawn_node.job = job
spawn_node.save()
logger.debug('Spawned %s in %s for node %s', job.log_format, workflow_job.log_format, spawn_node.pk)
can_start = True
if isinstance(spawn_node.unified_job_template, WorkflowJobTemplate):
workflow_ancestors = job.get_ancestor_workflows()
if spawn_node.unified_job_template in set(workflow_ancestors):
can_start = False
logger.info(
'Refusing to start recursive workflow-in-workflow id={}, wfjt={}, ancestors={}'.format(
job.id, spawn_node.unified_job_template.pk, [wa.pk for wa in workflow_ancestors]
)
)
display_list = [spawn_node.unified_job_template] + workflow_ancestors
job.job_explanation = gettext_noop(
"Workflow Job spawned from workflow could not start because it " "would result in recursion (spawn order, most recent first: {})"
).format(', '.join(['<{}>'.format(tmp) for tmp in display_list]))
else:
logger.debug(
'Starting workflow-in-workflow id={}, wfjt={}, ancestors={}'.format(
job.id, spawn_node.unified_job_template.pk, [wa.pk for wa in workflow_ancestors]
)
)
if not job._resources_sufficient_for_launch():
can_start = False
job.job_explanation = gettext_noop(
"Job spawned from workflow could not start because it " "was missing a related resource such as project or inventory"
)
if can_start:
if workflow_job.start_args:
start_args = json.loads(decrypt_field(workflow_job, 'start_args'))
else:
start_args = {}
can_start = job.signal_start(**start_args)
if not can_start:
job.job_explanation = gettext_noop(
"Job spawned from workflow could not start because it " "was not in the right state or required manual credentials"
)
if not can_start:
job.status = 'failed'
job.save(update_fields=['status', 'job_explanation'])
job.websocket_emit_status('failed')
def workflow_dag_canceled(self, wf_node_generator):
g = WorkflowDAG()
nodes = [wf_node_generator() for i in range(1)]
for n in nodes:
g.add_node(n)
r'''
F0
'''
nodes[0].job = Job(status='canceled')
return (g, nodes)
def test_build_WFJT_dag(self):
'''
Test that building the graph uses 4 queries
1 to get the nodes
3 to get the related success, failure, and always connections
'''
dag = WorkflowDAG()
wfj = self.workflow_job()
with self.assertNumQueries(4):
dag._init_graph(wfj)
def simple_all_convergence(self, wf_node_generator):
g = WorkflowDAG()
nodes = [wf_node_generator() for i in range(4)]
for n in nodes:
g.add_node(n)
r'''
0
/\
S / \ S
/ \
1 2
\ /
F \ / S
\/
3
'''
g.add_edge(nodes[0], nodes[1], "success_nodes")
g.add_edge(nodes[0], nodes[2], "success_nodes")
g.add_edge(nodes[1], nodes[3], "failure_nodes")
g.add_edge(nodes[2], nodes[3], "success_nodes")
nodes[3].all_parents_must_converge = True
nodes[0].job = Job(status='successful')
nodes[1].job = Job(status='failed')
nodes[2].job = Job(status='successful')
return (g, nodes)
def workflow_dag_1(wf_node_generator):
g = WorkflowDAG()
nodes = [wf_node_generator() for i in range(4)]
for n in nodes:
g.add_node(n)
r'''
0
/\
S / \
/ \
1 |
| |
F | | S
| |
3 |
\ |
F \ |
\/
2
'''
g.add_edge(nodes[0], nodes[1], "success_nodes")
g.add_edge(nodes[0], nodes[2], "success_nodes")
g.add_edge(nodes[1], nodes[3], "failure_nodes")
g.add_edge(nodes[3], nodes[2], "failure_nodes")
return (g, nodes)
def spawn_workflow_graph_jobs(self, workflow_jobs):
for workflow_job in workflow_jobs:
if workflow_job.cancel_flag:
logger.debug(
'Not spawning jobs for %s because it is pending cancelation.',
workflow_job.log_format)
continue
dag = WorkflowDAG(workflow_job)
spawn_nodes = dag.bfs_nodes_to_run()
if spawn_nodes:
logger.info('Spawning jobs for %s', workflow_job.log_format)
else:
logger.debug('No nodes to spawn for %s',
workflow_job.log_format)
for spawn_node in spawn_nodes:
if spawn_node.unified_job_template is None:
continue
kv = spawn_node.get_job_kwargs()
job = spawn_node.unified_job_template.create_unified_job(**kv)
spawn_node.job = job
spawn_node.save()
logger.info('Spawned %s in %s for node %s', job.log_format,
workflow_job.log_format, spawn_node.pk)
if job._resources_sufficient_for_launch():
if workflow_job.start_args:
start_args = json.loads(
decrypt_field(workflow_job, 'start_args'))
else:
start_args = {}
can_start = job.signal_start(**start_args)
if not can_start:
job.job_explanation = _(
"Job spawned from workflow could not start because it "
"was not in the right state or required manual credentials"
)
else:
can_start = False
job.job_explanation = _(
"Job spawned from workflow could not start because it "
"was missing a related resource such as project or inventory"
)
if not can_start:
job.status = 'failed'
job.save(update_fields=['status', 'job_explanation'])
connection.on_commit(
lambda: job.websocket_emit_status('failed'))
def workflow_dag_canceled(self, wf_node_generator):
g = WorkflowDAG()
nodes = [wf_node_generator() for i in range(4)]
for n in nodes:
g.add_node(n)
r'''
C0
/ | \
F / A| \ S
/ | \
1 2 3
'''
g.add_edge(nodes[0], nodes[1], "failure_nodes")
g.add_edge(nodes[0], nodes[2], "always_nodes")
g.add_edge(nodes[0], nodes[3], "success_nodes")
nodes[0].job = Job(status='canceled')
return (g, nodes)
def process_finished_workflow_jobs(self, workflow_jobs):
result = []
for workflow_job in workflow_jobs:
dag = WorkflowDAG(workflow_job)
if workflow_job.cancel_flag:
workflow_job.status = 'canceled'
workflow_job.save()
dag.cancel_node_jobs()
connection.on_commit(lambda: workflow_job.websocket_emit_status(workflow_job.status))
else:
is_done, has_failed = dag.is_workflow_done()
if not is_done:
continue
result.append(workflow_job.id)
workflow_job.status = 'failed' if has_failed else 'successful'
workflow_job.save()
connection.on_commit(lambda: workflow_job.websocket_emit_status(workflow_job.status))
return result
def test_workflow_fails_for_no_error_handler(self):
wfj = self.workflow_job(states=['successful', 'failed', None, None, None])
dag = WorkflowDAG(workflow_job=wfj)
dag.mark_dnr_nodes()
is_done = dag.is_workflow_done()
has_failed = dag.has_workflow_failed()
self.assertTrue(is_done)
self.assertTrue(has_failed)
def test_workflow_not_finished(self):
wfj = self.workflow_job(states=['new', None, None, None, None])
dag = WorkflowDAG(workflow_job=wfj)
dag.mark_dnr_nodes()
is_done = dag.is_workflow_done()
has_failed, reason = dag.has_workflow_failed()
self.assertFalse(is_done)
self.assertFalse(has_failed)
assert reason is None
def process_finished_workflow_jobs(self, workflow_jobs):
result = []
for workflow_job in workflow_jobs:
dag = WorkflowDAG(workflow_job)
status_changed = False
if workflow_job.cancel_flag:
workflow_job.workflow_nodes.filter(
do_not_run=False, job__isnull=True).update(do_not_run=True)
logger.debug(
'Canceling spawned jobs of %s due to cancel flag.',
workflow_job.log_format)
cancel_finished = dag.cancel_node_jobs()
if cancel_finished:
logger.info(
'Marking %s as canceled, all spawned jobs have concluded.',
workflow_job.log_format)
workflow_job.status = 'canceled'
workflow_job.start_args = '' # blank field to remove encrypted passwords
workflow_job.save(update_fields=['status', 'start_args'])
status_changed = True
else:
workflow_nodes = dag.mark_dnr_nodes()
for n in workflow_nodes:
n.save(update_fields=['do_not_run'])
is_done = dag.is_workflow_done()
if not is_done:
continue
has_failed, reason = dag.has_workflow_failed()
logger.debug('Marking %s as %s.', workflow_job.log_format,
'failed' if has_failed else 'successful')
result.append(workflow_job.id)
new_status = 'failed' if has_failed else 'successful'
logger.debug("Transitioning {} to {} status.".format(
workflow_job.log_format, new_status))
update_fields = ['status', 'start_args']
workflow_job.status = new_status
if reason:
logger.info(
f'Workflow job {workflow_job.id} failed due to reason: {reason}'
)
workflow_job.job_explanation = gettext_noop(
"No error handling paths found, marking workflow as failed"
)
update_fields.append('job_explanation')
workflow_job.start_args = '' # blank field to remove encrypted passwords
workflow_job.save(update_fields=update_fields)
status_changed = True
if status_changed:
workflow_job.websocket_emit_status(workflow_job.status)
# Operations whose queries rely on modifications made during the atomic scheduling session
workflow_job.send_notification_templates(
'succeeded' if workflow_job.status ==
'successful' else 'failed')
if workflow_job.spawned_by_workflow:
schedule_task_manager()
return result
def workflow_all_converge_1(self, wf_node_generator):
g = WorkflowDAG()
nodes = [wf_node_generator() for i in range(3)]
for n in nodes:
g.add_node(n)
r'''
0
|\ F
| \
S| 1
| /
|/ A
2
'''
g.add_edge(nodes[0], nodes[1], "failure_nodes")
g.add_edge(nodes[0], nodes[2], "success_nodes")
g.add_edge(nodes[1], nodes[2], "always_nodes")
nodes[2].all_parents_must_converge = True
nodes[0].job = Job(status='successful')
return (g, nodes)
def process_finished_workflow_jobs(self, workflow_jobs):
result = []
for workflow_job in workflow_jobs:
dag = WorkflowDAG(workflow_job)
status_changed = False
if workflow_job.cancel_flag:
workflow_job.workflow_nodes.filter(
do_not_run=False, job__isnull=True).update(do_not_run=True)
logger.debug(
'Canceling spawned jobs of %s due to cancel flag.',
workflow_job.log_format)
cancel_finished = dag.cancel_node_jobs()
if cancel_finished:
logger.info(
'Marking %s as canceled, all spawned jobs have concluded.',
workflow_job.log_format)
workflow_job.status = 'canceled'
workflow_job.start_args = '' # blank field to remove encrypted passwords
workflow_job.save(update_fields=['status', 'start_args'])
status_changed = True
else:
workflow_nodes = dag.mark_dnr_nodes()
map(lambda n: n.save(update_fields=['do_not_run']),
workflow_nodes)
is_done = dag.is_workflow_done()
if not is_done:
continue
has_failed, reason = dag.has_workflow_failed()
logger.info('Marking %s as %s.', workflow_job.log_format,
'failed' if has_failed else 'successful')
result.append(workflow_job.id)
new_status = 'failed' if has_failed else 'successful'
logger.debug(
six.text_type("Transitioning {} to {} status.").format(
workflow_job.log_format, new_status))
update_fields = ['status', 'start_args']
workflow_job.status = new_status
if reason:
logger.info(reason)
workflow_job.job_explanation = "No error handling paths found, marking workflow as failed"
update_fields.append('job_explanation')
workflow_job.start_args = '' # blank field to remove encrypted passwords
workflow_job.save(update_fields=update_fields)
status_changed = True
if status_changed:
workflow_job.websocket_emit_status(workflow_job.status)
if workflow_job.spawned_by_workflow:
schedule_task_manager()
return result
def test_workflow_done(self):
wfj = self.workflow_job(states=['failed', None, None, 'successful', None])
dag = WorkflowDAG(workflow_job=wfj)
is_done, has_failed = dag.is_workflow_done()
self.assertTrue(is_done)
self.assertFalse(has_failed)
# verify that relaunched WFJ fails if a JT leaf is deleted
for jt in JobTemplate.objects.all():
jt.delete()
relaunched = wfj.create_relaunch_workflow_job()
dag = WorkflowDAG(workflow_job=relaunched)
is_done, has_failed = dag.is_workflow_done()
self.assertTrue(is_done)
self.assertTrue(has_failed)
def workflow_all_converge_dnr(self, wf_node_generator):
g = WorkflowDAG()
nodes = [wf_node_generator() for i in range(4)]
for n in nodes:
g.add_node(n)
r'''
0 1 2
S \ F | / F
\ | /
\ | /
\|/
|
3
'''
g.add_edge(nodes[0], nodes[3], "success_nodes")
g.add_edge(nodes[1], nodes[3], "failure_nodes")
g.add_edge(nodes[2], nodes[3], "failure_nodes")
nodes[3].all_parents_must_converge = True
nodes[0].job = Job(status='successful')
nodes[1].job = Job(status='running')
nodes[2].job = Job(status='failed')
return (g, nodes)
def workflow_all_converge_2(self, wf_node_generator):
"""The ordering of _1 and this test, _2, is _slightly_ different.
The hope is that topological sorting results in 2 being processed before 3
and/or 3 before 2.
"""
g = WorkflowDAG()
nodes = [wf_node_generator() for i in range(3)]
for n in nodes:
g.add_node(n)
r'''
0
|\ S
| \
F| 1
| /
|/ A
2
'''
g.add_edge(nodes[0], nodes[1], "success_nodes")
g.add_edge(nodes[0], nodes[2], "failure_nodes")
g.add_edge(nodes[1], nodes[2], "always_nodes")
nodes[2].all_parents_must_converge = True
nodes[0].job = Job(status='successful')
return (g, nodes)
def workflow_dag_root_children(self, wf_node_generator):
g = WorkflowDAG()
wf_root_nodes = [wf_node_generator() for i in range(0, 10)]
wf_leaf_nodes = [wf_node_generator() for i in range(0, 10)]
for n in wf_root_nodes + wf_leaf_nodes:
g.add_node(n)
'''
Pair up a root node with a single child via an edge
R1 R2 ... Rx
| | |
| | |
C1 C2 Cx
'''
for i, n in enumerate(wf_leaf_nodes):
g.add_edge(wf_root_nodes[i], n, 'label')
return (g, wf_root_nodes, wf_leaf_nodes)
def test_workflow_done(self):
wfj = self.workflow_job(
states=['failed', None, None, 'successful', None])
dag = WorkflowDAG(workflow_job=wfj)
assert 3 == len(dag.mark_dnr_nodes())
is_done = dag.is_workflow_done()
has_failed, reason = dag.has_workflow_failed()
self.assertTrue(is_done)
self.assertFalse(has_failed)
assert reason is None
# verify that relaunched WFJ fails if a JT leaf is deleted
for jt in JobTemplate.objects.all():
jt.delete()
relaunched = wfj.create_relaunch_workflow_job()
dag = WorkflowDAG(workflow_job=relaunched)
dag.mark_dnr_nodes()
is_done = dag.is_workflow_done()
has_failed, reason = dag.has_workflow_failed()
self.assertTrue(is_done)
self.assertTrue(has_failed)
assert "Workflow job node {} related unified job template missing".format(
wfj.workflow_nodes.all()[0].id)
def test_workflow_fails_for_unfinished_node(self):
wfj = self.workflow_job(states=['error', None, None, None, None])
dag = WorkflowDAG(workflow_job=wfj)
is_done, has_failed = dag.is_workflow_done()
self.assertTrue(is_done)
self.assertTrue(has_failed)
def test_workflow_not_finished(self):
wfj = self.workflow_job(states=['new', None, None, None, None])
dag = WorkflowDAG(workflow_job=wfj)
is_done, has_failed = dag.is_workflow_done()
self.assertFalse(is_done)
self.assertFalse(has_failed)
def spawn_workflow_graph_jobs(self):
result = []
for workflow_job in self.all_tasks:
if self.timed_out():
logger.warning(
"Workflow manager has reached time out while processing running workflows, exiting loop early"
)
ScheduleWorkflowManager().schedule()
# Do not process any more workflow jobs. Stop here.
# Maybe we should schedule another WorkflowManager run
break
dag = WorkflowDAG(workflow_job)
status_changed = False
if workflow_job.cancel_flag:
workflow_job.workflow_nodes.filter(
do_not_run=False, job__isnull=True).update(do_not_run=True)
logger.debug(
'Canceling spawned jobs of %s due to cancel flag.',
workflow_job.log_format)
cancel_finished = dag.cancel_node_jobs()
if cancel_finished:
logger.info(
'Marking %s as canceled, all spawned jobs have concluded.',
workflow_job.log_format)
workflow_job.status = 'canceled'
workflow_job.start_args = '' # blank field to remove encrypted passwords
workflow_job.save(update_fields=['status', 'start_args'])
status_changed = True
else:
workflow_nodes = dag.mark_dnr_nodes()
WorkflowJobNode.objects.bulk_update(workflow_nodes,
['do_not_run'])
# If workflow is now done, we do special things to mark it as done.
is_done = dag.is_workflow_done()
if is_done:
has_failed, reason = dag.has_workflow_failed()
logger.debug('Marking %s as %s.', workflow_job.log_format,
'failed' if has_failed else 'successful')
result.append(workflow_job.id)
new_status = 'failed' if has_failed else 'successful'
logger.debug("Transitioning {} to {} status.".format(
workflow_job.log_format, new_status))
update_fields = ['status', 'start_args']
workflow_job.status = new_status
if reason:
logger.info(
f'Workflow job {workflow_job.id} failed due to reason: {reason}'
)
workflow_job.job_explanation = gettext_noop(
"No error handling paths found, marking workflow as failed"
)
update_fields.append('job_explanation')
workflow_job.start_args = '' # blank field to remove encrypted passwords
workflow_job.save(update_fields=update_fields)
status_changed = True
if status_changed:
if workflow_job.spawned_by_workflow:
ScheduleWorkflowManager().schedule()
workflow_job.websocket_emit_status(workflow_job.status)
# Operations whose queries rely on modifications made during the atomic scheduling session
workflow_job.send_notification_templates(
'succeeded' if workflow_job.status ==
'successful' else 'failed')
if workflow_job.status == 'running':
spawn_nodes = dag.bfs_nodes_to_run()
if spawn_nodes:
logger.debug('Spawning jobs for %s',
workflow_job.log_format)
else:
logger.debug('No nodes to spawn for %s',
workflow_job.log_format)
for spawn_node in spawn_nodes:
if spawn_node.unified_job_template is None:
continue
kv = spawn_node.get_job_kwargs()
job = spawn_node.unified_job_template.create_unified_job(
**kv)
spawn_node.job = job
spawn_node.save()
logger.debug('Spawned %s in %s for node %s',
job.log_format, workflow_job.log_format,
spawn_node.pk)
can_start = True
if isinstance(spawn_node.unified_job_template,
WorkflowJobTemplate):
workflow_ancestors = job.get_ancestor_workflows()
if spawn_node.unified_job_template in set(
workflow_ancestors):
can_start = False
logger.info(
'Refusing to start recursive workflow-in-workflow id={}, wfjt={}, ancestors={}'
.format(job.id,
spawn_node.unified_job_template.pk,
[wa.pk for wa in workflow_ancestors]))
display_list = [spawn_node.unified_job_template
] + workflow_ancestors
job.job_explanation = gettext_noop(
"Workflow Job spawned from workflow could not start because it "
"would result in recursion (spawn order, most recent first: {})"
).format(', '.join('<{}>'.format(tmp)
for tmp in display_list))
else:
logger.debug(
'Starting workflow-in-workflow id={}, wfjt={}, ancestors={}'
.format(job.id,
spawn_node.unified_job_template.pk,
[wa.pk for wa in workflow_ancestors]))
if not job._resources_sufficient_for_launch():
can_start = False
job.job_explanation = gettext_noop(
"Job spawned from workflow could not start because it was missing a related resource such as project or inventory"
)
if can_start:
if workflow_job.start_args:
start_args = json.loads(
decrypt_field(workflow_job, 'start_args'))
else:
start_args = {}
can_start = job.signal_start(**start_args)
if not can_start:
job.job_explanation = gettext_noop(
"Job spawned from workflow could not start because it was not in the right state or required manual credentials"
)
if not can_start:
job.status = 'failed'
job.save(update_fields=['status', 'job_explanation'])
job.websocket_emit_status('failed')
# TODO: should we emit a status on the socket here similar to tasks.py awx_periodic_scheduler() ?
# emit_websocket_notification('/socket.io/jobs', '', dict(id=))
return result
def workflow_all_converge_deep_dnr_tree(self, wf_node_generator):
g = WorkflowDAG()
nodes = [wf_node_generator() for i in range(7)]
for n in nodes:
g.add_node(n)
r'''
0 1 2
\ | /
S \ S| / F
\ | /
\|/
|
3
/\
S / \ S
/ \
4| | 5
\ /
S \ / S
\/
6
'''
g.add_edge(nodes[0], nodes[3], "success_nodes")
g.add_edge(nodes[1], nodes[3], "success_nodes")
g.add_edge(nodes[2], nodes[3], "failure_nodes")
g.add_edge(nodes[3], nodes[4], "success_nodes")
g.add_edge(nodes[3], nodes[5], "success_nodes")
g.add_edge(nodes[4], nodes[6], "success_nodes")
g.add_edge(nodes[5], nodes[6], "success_nodes")
nodes[3].all_parents_must_converge = True
nodes[4].all_parents_must_converge = True
nodes[5].all_parents_must_converge = True
nodes[6].all_parents_must_converge = True
nodes[0].job = Job(status='successful')
nodes[1].job = Job(status='successful')
nodes[2].job = Job(status='successful')
return (g, nodes)
def complex_dag(self, wf_node_generator):
g = WorkflowDAG()
nodes = [wf_node_generator() for i in range(10)]
for n in nodes:
g.add_node(n)
g.add_edge(nodes[0], nodes[1], "failure_nodes")
g.add_edge(nodes[0], nodes[2], "success_nodes")
g.add_edge(nodes[0], nodes[3], "always_nodes")
g.add_edge(nodes[1], nodes[4], "success_nodes")
g.add_edge(nodes[1], nodes[5], "failure_nodes")
g.add_edge(nodes[2], nodes[6], "failure_nodes")
g.add_edge(nodes[3], nodes[6], "success_nodes")
g.add_edge(nodes[4], nodes[6], "always_nodes")
g.add_edge(nodes[6], nodes[7], "always_nodes")
g.add_edge(nodes[6], nodes[8], "success_nodes")
g.add_edge(nodes[6], nodes[9], "failure_nodes")
return (g, nodes)
