forked from mirrors/gecko-dev
e07398454b
Certain tasks are meant to perform follow-up work to another task. For example, a 'signing' task signs an artifact from a dependency task. An 'upload-symbols' tasks uploads an artifact from a dependency task. In general, we only want to run these types of tasks when the dependency task is running. But in practice, these tasks often cause the dependency to get pulled in. We've tried to fix this in the past by making the 'run-on-projects' and 'optimization' keys match their primary dependency. But it's very easy to mess this up, and some optimizations (like bugbug) take the content of the task definition into account. So even if both tasks use the same optimization, they could have different results. This revision adds a new 'if-dependencies' key that denotes a task that should only run if one of the dependencies specified in this list is also run. It will allow us to stop playing whack-a-mole when trying to make sure tasks aren't being pulled in solely due to these types of dependencies. This feature is implemented independently of the 'optimization', so tasks that specify this can still be optimized even if their primary dependency does run. Differential Revision: https://phabricator.services.mozilla.com/D80508
434 lines
16 KiB
Python
434 lines
16 KiB
Python
# 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 logging
|
|
import os
|
|
import copy
|
|
import attr
|
|
import six
|
|
from six import text_type, ensure_text
|
|
|
|
from . import filter_tasks
|
|
from .graph import Graph
|
|
from .taskgraph import TaskGraph
|
|
from .task import Task
|
|
from .optimize import optimize_task_graph
|
|
from .morph import morph
|
|
from .parameters import Parameters
|
|
from .util.python_path import find_object
|
|
from .transforms.base import TransformSequence, TransformConfig
|
|
from .util.verify import (
|
|
verify_docs,
|
|
verifications,
|
|
)
|
|
from .util.yaml import load_yaml
|
|
from .config import load_graph_config, GraphConfig
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
class KindNotFound(Exception):
|
|
"""
|
|
Raised when trying to load kind from a directory without a kind.yml.
|
|
"""
|
|
|
|
|
|
@attr.s(frozen=True)
|
|
class Kind(object):
|
|
|
|
name = attr.ib(type=text_type)
|
|
path = attr.ib(type=text_type)
|
|
config = attr.ib(type=dict)
|
|
graph_config = attr.ib(type=GraphConfig)
|
|
|
|
def _get_loader(self):
|
|
try:
|
|
loader = self.config['loader']
|
|
except KeyError:
|
|
raise KeyError("{!r} does not define `loader`".format(self.path))
|
|
return find_object(loader)
|
|
|
|
def load_tasks(self, parameters, loaded_tasks, write_artifacts):
|
|
loader = self._get_loader()
|
|
config = copy.deepcopy(self.config)
|
|
|
|
kind_dependencies = config.get('kind-dependencies', [])
|
|
kind_dependencies_tasks = {task.label: task for task in loaded_tasks
|
|
if task.kind in kind_dependencies}
|
|
|
|
inputs = loader(self.name, self.path, config, parameters, loaded_tasks)
|
|
|
|
transforms = TransformSequence()
|
|
for xform_path in config['transforms']:
|
|
transform = find_object(xform_path)
|
|
transforms.add(transform)
|
|
|
|
# perform the transformations on the loaded inputs
|
|
trans_config = TransformConfig(self.name, self.path, config, parameters,
|
|
kind_dependencies_tasks, self.graph_config,
|
|
write_artifacts=write_artifacts)
|
|
tasks = [Task(self.name,
|
|
label=task_dict['label'],
|
|
description=task_dict['description'],
|
|
attributes=task_dict['attributes'],
|
|
task=task_dict['task'],
|
|
optimization=task_dict.get('optimization'),
|
|
dependencies=task_dict.get('dependencies'),
|
|
soft_dependencies=task_dict.get('soft-dependencies'),
|
|
if_dependencies=task_dict.get('if-dependencies'),
|
|
release_artifacts=task_dict.get('release-artifacts'),
|
|
)
|
|
for task_dict in transforms(trans_config, inputs)]
|
|
return tasks
|
|
|
|
@classmethod
|
|
def load(cls, root_dir, graph_config, kind_name):
|
|
path = os.path.join(root_dir, kind_name)
|
|
kind_yml = os.path.join(path, 'kind.yml')
|
|
if not os.path.exists(kind_yml):
|
|
raise KindNotFound(kind_yml)
|
|
|
|
logger.debug("loading kind `{}` from `{}`".format(kind_name, path))
|
|
config = load_yaml(kind_yml)
|
|
|
|
return cls(kind_name, path, config, graph_config)
|
|
|
|
|
|
class TaskGraphGenerator(object):
|
|
"""
|
|
The central controller for taskgraph. This handles all phases of graph
|
|
generation. The task is generated from all of the kinds defined in
|
|
subdirectories of the generator's root directory.
|
|
|
|
Access to the results of this generation, as well as intermediate values at
|
|
various phases of generation, is available via properties. This encourages
|
|
the provision of all generation inputs at instance construction time.
|
|
"""
|
|
|
|
# Task-graph generation is implemented as a Python generator that yields
|
|
# each "phase" of generation. This allows some mach subcommands to short-
|
|
# circuit generation of the entire graph by never completing the generator.
|
|
|
|
def __init__(
|
|
self,
|
|
root_dir,
|
|
parameters,
|
|
decision_task_id="DECISION-TASK",
|
|
write_artifacts=False,
|
|
):
|
|
"""
|
|
@param root_dir: root directory, with subdirectories for each kind
|
|
@param paramaters: parameters for this task-graph generation, or callable
|
|
taking a `GraphConfig` and returning parameters
|
|
@type parameters: Union[Parameters, Callable[[GraphConfig], Parameters]]
|
|
"""
|
|
if root_dir is None:
|
|
root_dir = 'taskcluster/ci'
|
|
self.root_dir = ensure_text(root_dir)
|
|
self._parameters = parameters
|
|
self._decision_task_id = decision_task_id
|
|
self._write_artifacts = write_artifacts
|
|
|
|
# start the generator
|
|
self._run = self._run()
|
|
self._run_results = {}
|
|
|
|
@property
|
|
def parameters(self):
|
|
"""
|
|
The properties used for this graph.
|
|
|
|
@type: Properties
|
|
"""
|
|
return self._run_until('parameters')
|
|
|
|
@property
|
|
def full_task_set(self):
|
|
"""
|
|
The full task set: all tasks defined by any kind (a graph without edges)
|
|
|
|
@type: TaskGraph
|
|
"""
|
|
return self._run_until('full_task_set')
|
|
|
|
@property
|
|
def full_task_graph(self):
|
|
"""
|
|
The full task graph: the full task set, with edges representing
|
|
dependencies.
|
|
|
|
@type: TaskGraph
|
|
"""
|
|
return self._run_until('full_task_graph')
|
|
|
|
@property
|
|
def target_task_set(self):
|
|
"""
|
|
The set of targetted tasks (a graph without edges)
|
|
|
|
@type: TaskGraph
|
|
"""
|
|
return self._run_until('target_task_set')
|
|
|
|
@property
|
|
def target_task_graph(self):
|
|
"""
|
|
The set of targetted tasks and all of their dependencies
|
|
|
|
@type: TaskGraph
|
|
"""
|
|
return self._run_until('target_task_graph')
|
|
|
|
@property
|
|
def optimized_task_graph(self):
|
|
"""
|
|
The set of targetted tasks and all of their dependencies; tasks that
|
|
have been optimized out are either omitted or replaced with a Task
|
|
instance containing only a task_id.
|
|
|
|
@type: TaskGraph
|
|
"""
|
|
return self._run_until('optimized_task_graph')
|
|
|
|
@property
|
|
def label_to_taskid(self):
|
|
"""
|
|
A dictionary mapping task label to assigned taskId. This property helps
|
|
in interpreting `optimized_task_graph`.
|
|
|
|
@type: dictionary
|
|
"""
|
|
return self._run_until('label_to_taskid')
|
|
|
|
@property
|
|
def morphed_task_graph(self):
|
|
"""
|
|
The optimized task graph, with any subsequent morphs applied. This graph
|
|
will have the same meaning as the optimized task graph, but be in a form
|
|
more palatable to TaskCluster.
|
|
|
|
@type: TaskGraph
|
|
"""
|
|
return self._run_until('morphed_task_graph')
|
|
|
|
@property
|
|
def graph_config(self):
|
|
"""
|
|
The configuration for this graph.
|
|
|
|
@type: TaskGraph
|
|
"""
|
|
return self._run_until('graph_config')
|
|
|
|
def _load_kinds(self, graph_config):
|
|
for kind_name in os.listdir(self.root_dir):
|
|
try:
|
|
yield Kind.load(self.root_dir, graph_config, kind_name)
|
|
except KindNotFound:
|
|
continue
|
|
|
|
def _run(self):
|
|
logger.info("Loading graph configuration.")
|
|
graph_config = load_graph_config(self.root_dir)
|
|
|
|
yield ('graph_config', graph_config)
|
|
|
|
graph_config.register()
|
|
|
|
if callable(self._parameters):
|
|
parameters = self._parameters(graph_config)
|
|
else:
|
|
parameters = self._parameters
|
|
self.verify_parameters(parameters)
|
|
|
|
filters = parameters.get('filters', [])
|
|
# Always add legacy target tasks method until we deprecate that API.
|
|
if 'target_tasks_method' not in filters:
|
|
filters.insert(0, 'target_tasks_method')
|
|
filters = [filter_tasks.filter_task_functions[f] for f in filters]
|
|
|
|
yield ('parameters', parameters)
|
|
|
|
logger.info("Loading kinds")
|
|
# put the kinds into a graph and sort topologically so that kinds are loaded
|
|
# in post-order
|
|
kinds = {kind.name: kind for kind in self._load_kinds(graph_config)}
|
|
self.verify_kinds(kinds)
|
|
|
|
edges = set()
|
|
for kind in six.itervalues(kinds):
|
|
for dep in kind.config.get('kind-dependencies', []):
|
|
edges.add((kind.name, dep, 'kind-dependency'))
|
|
kind_graph = Graph(set(kinds), edges)
|
|
|
|
if parameters.get('target-kind'):
|
|
target_kind = parameters['target-kind']
|
|
logger.info(
|
|
"Limiting kinds to {target_kind} and dependencies".format(
|
|
target_kind=target_kind))
|
|
kind_graph = kind_graph.transitive_closure({target_kind, 'docker-image'})
|
|
|
|
logger.info("Generating full task set")
|
|
all_tasks = {}
|
|
for kind_name in kind_graph.visit_postorder():
|
|
logger.debug("Loading tasks for kind {}".format(kind_name))
|
|
kind = kinds[kind_name]
|
|
try:
|
|
new_tasks = kind.load_tasks(
|
|
parameters, list(all_tasks.values()), self._write_artifacts,
|
|
)
|
|
except Exception:
|
|
logger.exception("Error loading tasks for kind {}:".format(kind_name))
|
|
raise
|
|
for task in new_tasks:
|
|
if task.label in all_tasks:
|
|
raise Exception("duplicate tasks with label " + task.label)
|
|
all_tasks[task.label] = task
|
|
logger.info("Generated {} tasks for kind {}".format(len(new_tasks), kind_name))
|
|
full_task_set = TaskGraph(all_tasks, Graph(set(all_tasks), set()))
|
|
self.verify_attributes(all_tasks)
|
|
self.verify_run_using()
|
|
yield verifications('full_task_set', full_task_set, graph_config, parameters)
|
|
|
|
logger.info("Generating full task graph")
|
|
edges = set()
|
|
for t in full_task_set:
|
|
for depname, dep in six.iteritems(t.dependencies):
|
|
edges.add((t.label, dep, depname))
|
|
|
|
full_task_graph = TaskGraph(all_tasks,
|
|
Graph(full_task_set.graph.nodes, edges))
|
|
logger.info("Full task graph contains %d tasks and %d dependencies" % (
|
|
len(full_task_set.graph.nodes), len(edges)))
|
|
yield verifications('full_task_graph', full_task_graph, graph_config, parameters)
|
|
|
|
logger.info("Generating target task set")
|
|
target_task_set = TaskGraph(dict(all_tasks),
|
|
Graph(set(all_tasks.keys()), set()))
|
|
for fltr in filters:
|
|
old_len = len(target_task_set.graph.nodes)
|
|
target_tasks = set(fltr(target_task_set, parameters, graph_config))
|
|
target_task_set = TaskGraph(
|
|
{l: all_tasks[l] for l in target_tasks},
|
|
Graph(target_tasks, set()))
|
|
logger.info('Filter %s pruned %d tasks (%d remain)' % (
|
|
fltr.__name__,
|
|
old_len - len(target_tasks),
|
|
len(target_tasks)))
|
|
|
|
yield verifications('target_task_set', target_task_set, graph_config, parameters)
|
|
|
|
logger.info("Generating target task graph")
|
|
# include all docker-image build tasks here, in case they are needed for a graph morph
|
|
docker_image_tasks = set(t.label for t in six.itervalues(full_task_graph.tasks)
|
|
if t.attributes['kind'] == 'docker-image')
|
|
# include all tasks with `always_target` set
|
|
if parameters["tasks_for"] == "hg-push":
|
|
always_target_tasks = set(t.label for t in six.itervalues(full_task_graph.tasks)
|
|
if t.attributes.get('always_target'))
|
|
else:
|
|
always_target_tasks = set()
|
|
logger.info('Adding %d tasks with `always_target` attribute' % (
|
|
len(always_target_tasks) - len(always_target_tasks & target_tasks)))
|
|
requested_tasks = target_tasks | docker_image_tasks | always_target_tasks
|
|
target_graph = full_task_graph.graph.transitive_closure(requested_tasks)
|
|
target_task_graph = TaskGraph(
|
|
{l: all_tasks[l] for l in target_graph.nodes},
|
|
target_graph)
|
|
yield verifications('target_task_graph', target_task_graph, graph_config, parameters)
|
|
|
|
logger.info("Generating optimized task graph")
|
|
existing_tasks = parameters.get('existing_tasks')
|
|
do_not_optimize = set(parameters.get('do_not_optimize', []))
|
|
if not parameters.get('optimize_target_tasks', True):
|
|
do_not_optimize = set(target_task_set.graph.nodes).union(do_not_optimize)
|
|
|
|
# this is used for testing experimental optimization strategies
|
|
strategies = os.environ.get('TASKGRAPH_OPTIMIZE_STRATEGIES',
|
|
parameters.get('optimize_strategies'))
|
|
if strategies:
|
|
strategies = find_object(strategies)
|
|
|
|
optimized_task_graph, label_to_taskid = optimize_task_graph(
|
|
target_task_graph,
|
|
requested_tasks,
|
|
parameters,
|
|
do_not_optimize,
|
|
self._decision_task_id,
|
|
existing_tasks=existing_tasks,
|
|
strategy_override=strategies,
|
|
)
|
|
|
|
yield verifications('optimized_task_graph', optimized_task_graph, graph_config, parameters)
|
|
|
|
morphed_task_graph, label_to_taskid = morph(
|
|
optimized_task_graph, label_to_taskid, parameters, graph_config,
|
|
self._decision_task_id)
|
|
|
|
yield 'label_to_taskid', label_to_taskid
|
|
yield verifications('morphed_task_graph', morphed_task_graph, graph_config, parameters)
|
|
|
|
def _run_until(self, name):
|
|
while name not in self._run_results:
|
|
try:
|
|
k, v = next(self._run)
|
|
except StopIteration:
|
|
raise AttributeError("No such run result {}".format(name))
|
|
self._run_results[k] = v
|
|
return self._run_results[name]
|
|
|
|
def verify_parameters(self, parameters):
|
|
if not parameters.strict:
|
|
return
|
|
|
|
parameters_dict = dict(**parameters)
|
|
verify_docs(
|
|
filename="parameters.rst",
|
|
identifiers=list(parameters_dict),
|
|
appearing_as="inline-literal"
|
|
)
|
|
|
|
def verify_kinds(self, kinds):
|
|
verify_docs(
|
|
filename="kinds.rst",
|
|
identifiers=kinds.keys(),
|
|
appearing_as="heading"
|
|
)
|
|
|
|
def verify_attributes(self, all_tasks):
|
|
attribute_set = set()
|
|
for label, task in six.iteritems(all_tasks):
|
|
attribute_set.update(task.attributes.keys())
|
|
verify_docs(
|
|
filename="attributes.rst",
|
|
identifiers=list(attribute_set),
|
|
appearing_as="heading"
|
|
)
|
|
|
|
def verify_run_using(self):
|
|
from .transforms.job import registry
|
|
verify_docs(
|
|
filename="transforms.rst",
|
|
identifiers=registry.keys(),
|
|
appearing_as="inline-literal"
|
|
)
|
|
|
|
|
|
def load_tasks_for_kind(parameters, kind, root_dir=None):
|
|
"""
|
|
Get all the tasks of a given kind.
|
|
|
|
This function is designed to be called from outside of taskgraph.
|
|
"""
|
|
# make parameters read-write
|
|
parameters = dict(parameters)
|
|
parameters['target-kind'] = kind
|
|
parameters = Parameters(strict=False, **parameters)
|
|
tgg = TaskGraphGenerator(root_dir=root_dir, parameters=parameters)
|
|
return {
|
|
task.task['metadata']['name']: task
|
|
for task in tgg.full_task_set
|
|
if task.kind == kind
|
|
}
|