def taskgraph_decision(options):
"""
Run the decision task. This function implements `mach taskgraph decision`,
and is responsible for
* processing decision task command-line options into parameters
* running task-graph generation exactly the same way the other `mach
taskgraph` commands do
* generating a set of artifacts to memorialize the graph
* calling TaskCluster APIs to create the graph
"""
parameters = get_decision_parameters(options)
# create a TaskGraphGenerator instance
tgg = TaskGraphGenerator(
root_dir=options['root'],
parameters=parameters)
# write out the parameters used to generate this graph
write_artifact('parameters.yml', dict(**parameters))
# write out the yml file for action tasks
write_artifact('action.yml', get_action_yml(parameters))
# write out the public/actions.json file
write_artifact('actions.json', render_actions_json(parameters))
# write out the full graph for reference
full_task_json = tgg.full_task_graph.to_json()
write_artifact('full-task-graph.json', full_task_json)
# this is just a test to check whether the from_json() function is working
_, _ = TaskGraph.from_json(full_task_json)
# write out the target task set to allow reproducing this as input
write_artifact('target-tasks.json', tgg.target_task_set.tasks.keys())
# write out the optimized task graph to describe what will actually happen,
# and the map of labels to taskids
write_artifact('task-graph.json', tgg.optimized_task_graph.to_json())
write_artifact('label-to-taskid.json', tgg.label_to_taskid)
# actually create the graph
create_tasks(tgg.optimized_task_graph, tgg.label_to_taskid, parameters)
def taskgraph_decision(options):
"""
Run the decision task. This function implements `mach taskgraph decision`,
and is responsible for
* processing decision task command-line options into parameters
* running task-graph generation exactly the same way the other `mach
taskgraph` commands do
* generating a set of artifacts to memorialize the graph
* calling TaskCluster APIs to create the graph
"""
parameters = get_decision_parameters(options)
# create a TaskGraphGenerator instance
tgg = TaskGraphGenerator(
root_dir=options['root'],
parameters=parameters)
# write out the parameters used to generate this graph
write_artifact('parameters.yml', dict(**parameters))
# write out the yml file for action tasks
write_artifact('action.yml', get_action_yml(parameters))
# write out the public/actions.json file
write_artifact('actions.json', render_actions_json(parameters))
# write out the full graph for reference
full_task_json = tgg.full_task_graph.to_json()
write_artifact('full-task-graph.json', full_task_json)
# this is just a test to check whether the from_json() function is working
_, _ = TaskGraph.from_json(full_task_json)
# write out the target task set to allow reproducing this as input
write_artifact('target-tasks.json', tgg.target_task_set.tasks.keys())
# write out the optimized task graph to describe what will actually happen,
# and the map of labels to taskids
write_artifact('task-graph.json', tgg.morphed_task_graph.to_json())
write_artifact('label-to-taskid.json', tgg.label_to_taskid)
# actually create the graph
create_tasks(tgg.morphed_task_graph, tgg.label_to_taskid, parameters)