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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/.
import attr
@attr.s
class Task:
"""
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)
- optimization: optimization to apply to the task (see taskgraph.optimize)
- dependencies: tasks this one depends on, in the form {name: label}, for example
{'build': 'build-linux64/opt', 'docker-image': 'build-docker-image-desktop-test'}
- soft_dependencies: tasks this one may depend on if they are available post
optimisation. They are set as a list of tasks label.
- if_dependencies: only run this task if at least one of these dependencies
are present.
And later, as the task-graph processing proceeds:
- task_id -- TaskCluster taskId under which this task will be created
This class is just a convenience wrapper for the data type and managing
display, comparison, serialization, etc. It has no functionality of its own.
"""
kind = attr.ib()
label = attr.ib()
attributes = attr.ib()
task = attr.ib()
description = attr.ib(default="")
task_id = attr.ib(default=None, init=False)
optimization = attr.ib(default=None)
dependencies = attr.ib(factory=dict)
soft_dependencies = attr.ib(factory=list)
if_dependencies = attr.ib(factory=list)
def __attrs_post_init__(self):
self.attributes["kind"] = self.kind
def to_json(self):
rv = {
"kind": self.kind,
"label": self.label,
"description": self.description,
"attributes": self.attributes,
"dependencies": self.dependencies,
"soft_dependencies": self.soft_dependencies,
"if_dependencies": self.if_dependencies,
"optimization": self.optimization,
"task": self.task,
}
if self.task_id:
rv["task_id"] = self.task_id
return rv
@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.
"""
rv = cls(
kind=task_dict["kind"],
label=task_dict["label"],
description=task_dict.get("description", ""),
attributes=task_dict["attributes"],
task=task_dict["task"],
optimization=task_dict["optimization"],
dependencies=task_dict.get("dependencies"),
soft_dependencies=task_dict.get("soft_dependencies"),
if_dependencies=task_dict.get("if_dependencies"),
)
if "task_id" in task_dict:
rv.task_id = task_dict["task_id"]
return rv
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