External-Mirrors/awx
2
0
Fork 0
mirror of https://github.com/ansible/awx.git synced 2026-01-11 18:09:57 -03:30
Code Issues Packages Projects Releases Wiki Activity

flake8 fixes

Browse Source
This commit is contained in:
Chris Meyers 2016-09-08 14:26:30 -04:00
parent 28ec68e91b
commit e4025a7eff
10 changed files with 60 additions and 74 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
awx/api/serializers.py
View File

@ -2187,7 +2187,7 @@ class WorkflowJobSerializer(UnifiedJobSerializer):
res = super(WorkflowJobSerializer, self).get_related(obj)
if obj.workflow_job_template:
res['workflow_job_template'] = reverse('api:workflow_job_template_detail',
args=(obj.workflow_job_template.pk,))
args=(obj.workflow_job_template.pk,))
# TODO:
#res['notifications'] = reverse('api:system_job_notifications_list', args=(obj.pk,))
res['workflow_nodes'] = reverse('api:workflow_job_workflow_nodes_list', args=(obj.pk,))

1
awx/api/views.py
View File

@ -11,7 +11,6 @@ import socket
import sys
import errno
import logging
import copy
from base64 import b64encode
from collections import OrderedDict

7
awx/main/access.py
View File

@ -1172,9 +1172,6 @@ class WorkflowJobTemplateAccess(BaseAccess):
model = WorkflowJobTemplate
def can_start(self, obj):
return self.can_read(obj)
def get_queryset(self):
if self.user.is_superuser or self.user.is_system_auditor:
qs = self.model.objects.all()
@ -1234,7 +1231,9 @@ class WorkflowJobTemplateAccess(BaseAccess):
if self.user.is_superuser:
return True
return self.user in obj.execute_role
return self.can_read(obj)
# TODO: We should use execute role rather than read role
#return self.user in obj.execute_role
def can_change(self, obj, data):
data_for_change = data

16
awx/main/management/commands/run_task_system.py
View File

@ -220,7 +220,7 @@ class WorkflowDAG(SimpleDAG):
children_always = self.get_dependencies(obj, 'always_nodes')
children_all = children_failed + children_always
nodes.extend(children_all)
elif job.status in ['successfult']:
elif job.status in ['successful']:
children_success = self.get_dependencies(obj, 'success_nodes')
nodes.extend(children_success)
else:
@ -260,12 +260,22 @@ def do_spawn_workflow_jobs():
dag = WorkflowDAG(workflow_job)
spawn_nodes = dag.bfs_nodes_to_run()
for spawn_node in spawn_nodes:
# TODO: Inject job template template params as kwargs
# TODO: Inject job template template params as kwargs.
# Make sure to take into account extra_vars merge logic
kv = {}
job = spawn_node.unified_job_template.create_unified_job(**kv)
spawn_node.job = job
spawn_node.save()
result = job.signal_start(**kv)
can_start = job.signal_start(**kv)
if not can_start:
job.status = 'failed'
job.job_explanation = "Workflow job could not start because it was not in the right state or required manual credentials"
job.save(update_fields=['status', 'job_explanation'])
job.socketio_emit_status("failed")
# TODO: should we emit a status on the socket here similar to tasks.py tower_periodic_scheduler() ?
#emit_websocket_notification('/socket.io/jobs', '', dict(id=))
def rebuild_graph(message):
"""Regenerate the task graph by refreshing known tasks from Tower, purging

8
awx/main/models/workflow.py
View File

@ -1,6 +1,9 @@
# Copyright (c) 2016 Ansible, Inc.
# All Rights Reserved.
# Python
#import urlparse
# Django
from django.db import models
from django.core.urlresolvers import reverse
@ -202,8 +205,9 @@ class WorkflowJob(UnifiedJob, WorkflowJobOptions, JobNotificationMixin, Workflow
def get_absolute_url(self):
return reverse('api:workflow_job_detail', args=(self.pk,))
def get_ui_url(self):
return urljoin(tower_settings.TOWER_URL_BASE, "/#/workflow_jobs/{}".format(self.pk))
# TODO: Ask UI if this is needed ?
#def get_ui_url(self):
# return urlparse.urljoin(tower_settings.TOWER_URL_BASE, "/#/workflow_jobs/{}".format(self.pk))
def is_blocked_by(self, obj):
return True

3
awx/main/tests/factories/fixtures.py
View File

@ -14,6 +14,7 @@ from awx.main.models import (
Inventory,
Label,
WorkflowJobTemplate,
WorkflowNode,
)
# mk methods should create only a single object of a single type.
@ -169,7 +170,7 @@ def mk_workflow_node(workflow_job_template=None, unified_job_template=None,
success_nodes=None, failure_nodes=None, always_nodes=None,
job=None, persisted=True):
workflow_node = WorkflowNode(workflow_job_template=workflow_job_template,
unified_job_template=job_template,
unified_job_template=unified_job_template,
success_nodes=success_nodes,
failure_nodes=failure_nodes,
always_nodes=always_nodes,

1
awx/main/tests/factories/tower.py
View File

@ -9,7 +9,6 @@ from awx.main.models import (
Inventory,
Job,
Label,
WorkflowJobTemplate,
)
from .objects import (

1
awx/main/tests/manual/workflows/linear.py
View File

@ -2,7 +2,6 @@
from awx.main.models import (
WorkflowNode,
WorkflowJobTemplate,
WorkflowJob,
)
from awx.main.models.jobs import JobTemplate

1
awx/main/tests/manual/workflows/parallel.py
View File

@ -2,7 +2,6 @@
from awx.main.models import (
WorkflowNode,
WorkflowJobTemplate,
WorkflowJob,
)
from awx.main.models.jobs import JobTemplate

94
awx/main/tests/unit/commands/test_run_task_system.py
View File

@ -10,12 +10,12 @@ import pytest
def dag_root():
dag = SimpleDAG()
data = [
{ 1: 1 },
{ 2: 2 },
{ 3: 3 },
{ 4: 4 },
{ 5: 5 },
{ 6: 6 },
{1: 1},
{2: 2},
{3: 3},
{4: 4},
{5: 5},
{6: 6},
]
# Add all the nodes to the DAG
[dag.add_node(d) for d in data]
@ -30,12 +30,12 @@ def dag_root():
def dag_simple_edge_labels():
dag = SimpleDAG()
data = [
{ 1: 1 },
{ 2: 2 },
{ 3: 3 },
{ 4: 4 },
{ 5: 5 },
{ 6: 6 },
{1: 1},
{2: 2},
{3: 3},
{4: 4},
{5: 5},
{6: 6},
]
# Add all the nodes to the DAG
[dag.add_node(d) for d in data]
@ -46,23 +46,18 @@ def dag_simple_edge_labels():
return dag
'''
class TestSimpleDAG(object):
def test_get_root_nodes(self, dag_root):
leafs = dag_root.get_leaf_nodes()
for l in leafs:
print(l)
roots = dag_root.get_root_nodes()
for n in roots:
print(n)
def test_get_labeled_edges(self, dag_simple_edge_labels):
dag = dag_simple_edge_labels
nodes = dag.get_dependencies(dag.nodes[0]['node_object'], 'one')
nodes = dag.get_dependencies(dag.nodes[0]['node_object'], 'two')
print("Matching nodes: ")
for n in nodes:
print(n)
'''
@pytest.fixture
def factory_node():
@ -74,41 +69,22 @@ def factory_node():
return wfn
return fn
@pytest.fixture
def workflow_dag_multiple_roots(factory_node):
dag = WorkflowDAG()
data = [
factory_node(1, None),
factory_node(2, None),
factory_node(3, None),
factory_node(4, None),
factory_node(5, None),
factory_node(6, None),
]
[dag.add_node(d) for d in data]
dag.add_edge(data[0], data[3], 'success')
dag.add_edge(data[1], data[4], 'success')
dag.add_edge(data[2], data[5], 'success')
return dag
@pytest.fixture
def workflow_dag_level_2(factory_node):
dag = WorkflowDAG()
data = [
factory_node(1, 'success'),
factory_node(2, 'success'),
factory_node(3, 'success'),
factory_node(0, 'successful'),
factory_node(1, 'successful'),
factory_node(2, 'successful'),
factory_node(3, None),
factory_node(4, None),
factory_node(5, None),
factory_node(6, None),
]
[dag.add_node(d) for d in data]
dag.add_edge(data[0], data[3], 'success')
dag.add_edge(data[1], data[4], 'success')
dag.add_edge(data[2], data[5], 'success')
dag.add_edge(data[0], data[3], 'success_nodes')
dag.add_edge(data[1], data[4], 'success_nodes')
dag.add_edge(data[2], data[5], 'success_nodes')
return (dag, data[3:6], False)
@ -125,9 +101,9 @@ def workflow_dag_multiple_roots(factory_node):
]
[dag.add_node(d) for d in data]
dag.add_edge(data[0], data[3], 'success')
dag.add_edge(data[1], data[4], 'success')
dag.add_edge(data[2], data[5], 'success')
dag.add_edge(data[0], data[3], 'success_nodes')
dag.add_edge(data[1], data[4], 'success_nodes')
dag.add_edge(data[2], data[5], 'success_nodes')
expected = data[0:3]
return (dag, expected, False)
@ -145,11 +121,11 @@ def workflow_dag_multiple_edges_labeled(factory_node):
]
[dag.add_node(d) for d in data]
dag.add_edge(data[0], data[1], 'success')
dag.add_edge(data[0], data[2], 'failure')
dag.add_edge(data[2], data[3], 'success')
dag.add_edge(data[2], data[4], 'failure')
dag.add_edge(data[4], data[5], 'failure')
dag.add_edge(data[0], data[1], 'success_nodes')
dag.add_edge(data[0], data[2], 'failure_nodes')
dag.add_edge(data[2], data[3], 'success_nodes')
dag.add_edge(data[2], data[4], 'failure_nodes')
dag.add_edge(data[4], data[5], 'failure_nodes')
expected = data[5:6]
return (dag, expected, False)
@ -163,15 +139,15 @@ def workflow_dag_finished(factory_node):
factory_node(2, 'failed'),
factory_node(3, None),
factory_node(4, 'failed'),
factory_node(5, 'success'),
factory_node(5, 'successful'),
]
[dag.add_node(d) for d in data]
dag.add_edge(data[0], data[1], 'success')
dag.add_edge(data[0], data[2], 'failure')
dag.add_edge(data[2], data[3], 'success')
dag.add_edge(data[2], data[4], 'failure')
dag.add_edge(data[4], data[5], 'failure')
dag.add_edge(data[0], data[1], 'success_nodes')
dag.add_edge(data[0], data[2], 'failure_nodes')
dag.add_edge(data[2], data[3], 'success_nodes')
dag.add_edge(data[2], data[4], 'failure_nodes')
dag.add_edge(data[4], data[5], 'failure_nodes')
expected = []
return (dag, expected, True)