gecko-dev/taskcluster/taskgraph/taskgraph.py

83 строки
2.9 KiB
Python
Исходник Обычный вид История

# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
from __future__ import absolute_import, print_function, unicode_literals
import os
from .graph import Graph
from .util.python_path import find_object
TASKCLUSTER_QUEUE_URL = "https://queue.taskcluster.net/v1/task/"
GECKO = os.path.realpath(os.path.join(__file__, '..', '..', '..'))
class TaskGraph(object):
"""
Representation of a task graph.
A task graph is a combination of a Graph and a dictionary of tasks indexed
by label. TaskGraph instances should be treated as immutable.
"""
def __init__(self, tasks, graph):
assert set(tasks) == graph.nodes
self.tasks = tasks
self.graph = graph
def to_json(self):
"Return a JSON-able object representing the task graph, as documented"
named_links_dict = self.graph.named_links_dict()
# this dictionary may be keyed by label or by taskid, so let's just call it 'key'
tasks = {}
for key in self.graph.visit_postorder():
task = self.tasks[key]
implementation = task.__class__.__module__ + ":" + task.__class__.__name__
task_json = {
'label': task.label,
'attributes': task.attributes,
'dependencies': named_links_dict.get(key, {}),
'task': task.task,
'kind_implementation': implementation
}
if task.task_id:
task_json['task_id'] = task.task_id
tasks[key] = task_json
return tasks
def __getitem__(self, label):
"Get a task by label"
return self.tasks[label]
def __iter__(self):
"Iterate over tasks in undefined order"
return self.tasks.itervalues()
def __repr__(self):
return "<TaskGraph graph={!r} tasks={!r}>".format(self.graph, self.tasks)
def __eq__(self, other):
return self.tasks == other.tasks and self.graph == other.graph
@classmethod
def from_json(cls, tasks_dict):
"""
This code is used to generate the a TaskGraph using a dictionary
which is representative of the TaskGraph.
"""
tasks = {}
edges = set()
for key, value in tasks_dict.iteritems():
# We get the implementation from JSON
implementation = value['kind_implementation']
# Loading the module and creating a Task from a dictionary
task_kind = find_object(implementation)
tasks[key] = task_kind.from_json(value)
if 'task_id' in value:
tasks[key].task_id = value['task_id']
for depname, dep in value['dependencies'].iteritems():
edges.add((key, dep, depname))
task_graph = cls(tasks, Graph(set(tasks), edges))
return tasks, task_graph