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# 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 abc
class Task(object):
"""
Representation of a task in a TaskGraph. Each Task has, at creation:
- kind: the name of the task kind
- label; the label for this task
- attributes: a dictionary of attributes for this task (used for filtering)
- task: the task definition (JSON-able dictionary)
And later, as the task-graph processing proceeds:
- task_id -- TaskCluster taskId under which this task will be created
- optimized -- true if this task need not be performed
A kind represents a collection of tasks that share common characteristics.
For example, all build jobs. Each instance of a kind is intialized with a
path from which it draws its task configuration. The instance is free to
store as much local state as it needs.
"""
__metaclass__ = abc.ABCMeta
def __init__(self, kind, label, attributes, task):
self.kind = kind
self.label = label
self.attributes = attributes
self.task = task
self.task_id = None
self.optimized = False
self.attributes['kind'] = kind
def __eq__(self, other):
return self.kind == other.kind and \
self.label == other.label and \
self.attributes == other.attributes and \
self.task == other.task and \
self.task_id == other.task_id
@classmethod
@abc.abstractmethod
def load_tasks(cls, kind, path, config, parameters, loaded_tasks):
"""
Load the tasks for a given kind.
The `kind` is the name of the kind; the configuration for that kind
named this class.
The `path` is the path to the configuration directory for the kind. This
can be used to load extra data, templates, etc.
The `parameters` give details on which to base the task generation.
See `taskcluster/docs/parameters.rst` for details.
At the time this method is called, all kinds on which this kind depends
(that is, specified in the `kind-dependencies` key in `self.config`
have already loaded their tasks, and those tasks are available in
the list `loaded_tasks`.
The return value is a list of Task instances.
"""
@abc.abstractmethod
def get_dependencies(self, taskgraph):
"""
Get the set of task labels this task depends on, by querying the full
task set, given as `taskgraph`.
Returns a list of (task_label, dependency_name) pairs describing the
dependencies.
"""
def optimize(self, params):
"""
Determine whether this task can be optimized, and if it can, what taskId
it should be replaced with.
The return value is a tuple `(optimized, taskId)`. If `optimized` is
true, then the task will be optimized (in other words, not included in
the task graph). If the second argument is a taskid, then any
dependencies on this task will isntead depend on that taskId. It is an
error to return no taskId for a task on which other tasks depend.
The default never optimizes.
"""
return False, None
@classmethod
def from_json(cls, task_dict):
"""
Given a data structure as produced by taskgraph.to_json, re-construct
the original Task object. This is used to "resume" the task-graph
generation process, for example in Action tasks.
"""
return cls(
kind=task_dict['attributes']['kind'],
label=task_dict['label'],
attributes=task_dict['attributes'],
task=task_dict['task'])
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