def test_parent_child(rk):
execution = next(rk)
t1 = Task.new({'name': '1', 'execution': execution})
t2 = Task.new({'name': '2', 'execution': execution})
t1.childs.add(t2)
t1.save()
t2.save()
assert Task.childs.filter(t1.key) == [t2.key]
assert Task.parents.filter(t2.key) == [t1.key]
assert t1.childs.all_tasks() == [t2]
assert t2.parents.all_names() == [t1.name]
def test_tasks_selected_by_execution_id(rk):
execution = next(rk)
for i in range(2):
t = Task.new({'name': str(i), 'execution': execution})
t.save()
another_execution = next(rk)
for i in range(2):
t = Task.new({'name': str(i), 'execution': another_execution})
t.save()
assert len(Task.execution.filter(execution)) == 2
assert len(Task.execution.filter(another_execution)) == 2
def save_graph(graph):
# maybe it is possible to store part of information in AsyncResult backend
uid = graph.graph['uid']
# TODO(dshulyak) remove duplication of parameters
# in solar_models.Task and this object
for n in nx.topological_sort(graph):
t = Task.new({
'name': n,
'execution': uid,
'status': graph.node[n].get('status', ''),
'target': graph.node[n].get('target', '') or '',
'task_type': graph.node[n].get('type', ''),
'args': graph.node[n].get('args', []),
'errmsg': graph.node[n].get('errmsg', '') or '',
'timelimit': graph.node[n].get('timelimit', 0),
'retry': graph.node[n].get('retry', 0),
'timeout': graph.node[n].get('timeout', 0),
'start_time': 0.0,
'end_time': 0.0
})
graph.node[n]['task'] = t
for pred in graph.predecessors(n):
pred_task = graph.node[pred]['task']
t.parents.add(pred_task)
pred_task.save()
t.save()
def save_graph(graph):
# maybe it is possible to store part of information in AsyncResult backend
uid = graph.graph['uid']
# TODO(dshulyak) remove duplication of parameters
# in solar_models.Task and this object
for n in nx.topological_sort(graph):
t = Task.new(
{'name': n,
'execution': uid,
'status': graph.node[n].get('status', ''),
'target': graph.node[n].get('target', '') or '',
'task_type': graph.node[n].get('type', ''),
'args': graph.node[n].get('args', []),
'errmsg': graph.node[n].get('errmsg', '') or '',
'timelimit': graph.node[n].get('timelimit', 0),
'retry': graph.node[n].get('retry', 0),
'timeout': graph.node[n].get('timeout', 0),
'start_time': 0.0,
'end_time': 0.0})
graph.node[n]['task'] = t
for pred in graph.predecessors(n):
pred_task = graph.node[pred]['task']
t.parents.add(pred_task)
pred_task.save()
t.save()
def get_graph(uid):
mdg = nx.MultiDiGraph()
mdg.graph['uid'] = uid
mdg.graph['name'] = uid.split(':')[0]
tasks_by_uid = {t.key: t for t
in Task.multi_get(Task.execution.filter(uid))}
mdg.add_nodes_from(tasks_by_uid.values())
mdg.add_edges_from([(tasks_by_uid[parent], task) for task in mdg.nodes()
for parent in task.parents.all()])
return mdg
def save_graph(graph):
for n in nx.topological_sort(graph):
values = {'name': n, 'execution': graph.graph['uid']}
values.update(graph.node[n])
t = Task.new(values)
graph.node[n]['task'] = t
for pred in graph.predecessors(n):
pred_task = graph.node[pred]['task']
t.parents.add(pred_task)
pred_task.save()
t.save_lazy()
def save_graph(graph):
# maybe it is possible to store part of information in AsyncResult backend
uid = graph.graph['uid']
for n in nx.topological_sort(graph):
t = Task.new(
{'name': n,
'execution': uid,
'status': graph.node[n].get('status', ''),
'target': graph.node[n].get('target', '') or '',
'task_type': graph.node[n].get('type', ''),
'args': graph.node[n].get('args', []),
'errmsg': graph.node[n].get('errmsg', '') or ''})
graph.node[n]['task'] = t
for pred in graph.predecessors(n):
pred_task = graph.node[pred]['task']
t.parents.add(pred_task)
pred_task.save()
t.save()
def save_graph(graph):
# maybe it is possible to store part of information in AsyncResult backend
uid = graph.graph['uid']
for n in nx.topological_sort(graph):
t = Task.new({
'name': n,
'execution': uid,
'status': graph.node[n].get('status', ''),
'target': graph.node[n].get('target', '') or '',
'task_type': graph.node[n].get('type', ''),
'args': graph.node[n].get('args', []),
'errmsg': graph.node[n].get('errmsg', '') or ''
})
graph.node[n]['task'] = t
for pred in graph.predecessors(n):
pred_task = graph.node[pred]['task']
t.parents.add(pred_task)
pred_task.save()
t.save()