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