gecko-dev/taskcluster/taskgraph/taskgraph.py

# 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

from .graph import Graph
from .task import Task


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 for_each_task(self, f, *args, **kwargs):
        for task_label in self.graph.visit_postorder():
            task = self.tasks[task_label]
            f(task, self, *args, **kwargs)

    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

    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():
            tasks[key] = self.tasks[key].to_json()
            # overwrite dependencies with the information in the taskgraph's edges.
            tasks[key]['dependencies'] = named_links_dict.get(key, {})
        return tasks

    @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():
            tasks[key] = Task.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