taskflow/taskflow/task.py

248 lines
9.8 KiB
Python

# -*- coding: utf-8 -*-
# Copyright 2015 Hewlett-Packard Development Company, L.P.
# Copyright (C) 2013 Rackspace Hosting Inc. All Rights Reserved.
# Copyright (C) 2013 Yahoo! Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import abc
import copy
import functools
from oslo_utils import reflection
from taskflow import atom
from taskflow import logging
from taskflow.types import notifier
from taskflow.utils import misc
LOG = logging.getLogger(__name__)
# Constants passed into revert kwargs.
#
# Contain the execute() result (if any).
REVERT_RESULT = 'result'
#
# The cause of the flow failure/s
REVERT_FLOW_FAILURES = 'flow_failures'
# Common events
EVENT_UPDATE_PROGRESS = 'update_progress'
class Task(atom.Atom, metaclass=abc.ABCMeta):
"""An abstraction that defines a potential piece of work.
This potential piece of work is expected to be able to contain
functionality that defines what can be executed to accomplish that work
as well as a way of defining what can be executed to reverted/undo that
same piece of work.
"""
# Known internal events this task can have callbacks bound to (others that
# are not in this set/tuple will not be able to be bound); this should be
# updated and/or extended in subclasses as needed to enable or disable new
# or existing internal events...
TASK_EVENTS = (EVENT_UPDATE_PROGRESS,)
def __init__(self, name=None, provides=None, requires=None,
auto_extract=True, rebind=None, inject=None,
ignore_list=None, revert_rebind=None, revert_requires=None):
if name is None:
name = reflection.get_class_name(self)
super(Task, self).__init__(name, provides=provides, requires=requires,
auto_extract=auto_extract, rebind=rebind,
inject=inject, revert_rebind=revert_rebind,
revert_requires=revert_requires)
self._notifier = notifier.RestrictedNotifier(self.TASK_EVENTS)
@property
def notifier(self):
"""Internal notification dispatcher/registry.
A notification object that will dispatch events that occur related
to *internal* notifications that the task internally emits to
listeners (for example for progress status updates, telling others
that a task has reached 50% completion...).
"""
return self._notifier
def copy(self, retain_listeners=True):
"""Clone/copy this task.
:param retain_listeners: retain the attached notification listeners
when cloning, when false the listeners will
be emptied, when true the listeners will be
copied and retained
:return: the copied task
"""
c = copy.copy(self)
c._notifier = self._notifier.copy()
if not retain_listeners:
c._notifier.reset()
return c
def update_progress(self, progress):
"""Update task progress and notify all registered listeners.
:param progress: task progress float value between 0.0 and 1.0
"""
def on_clamped():
LOG.warning("Progress value must be greater or equal to 0.0 or"
" less than or equal to 1.0 instead of being '%s'",
progress)
cleaned_progress = misc.clamp(progress, 0.0, 1.0,
on_clamped=on_clamped)
self._notifier.notify(EVENT_UPDATE_PROGRESS,
{'progress': cleaned_progress})
class FunctorTask(Task):
"""Adaptor to make a task from a callable.
Take any callable pair and make a task from it.
NOTE(harlowja): If a name is not provided the function/method name of
the ``execute`` callable will be used as the name instead (the name of
the ``revert`` callable is not used).
"""
def __init__(self, execute, name=None, provides=None,
requires=None, auto_extract=True, rebind=None, revert=None,
version=None, inject=None):
if not callable(execute):
raise ValueError("Function to use for executing must be"
" callable")
if revert is not None:
if not callable(revert):
raise ValueError("Function to use for reverting must"
" be callable")
if name is None:
name = reflection.get_callable_name(execute)
super(FunctorTask, self).__init__(name, provides=provides,
inject=inject)
self._execute = execute
self._revert = revert
if version is not None:
self.version = version
mapping = self._build_arg_mapping(execute, requires, rebind,
auto_extract)
self.rebind, exec_requires, self.optional = mapping
if revert:
revert_mapping = self._build_arg_mapping(revert, requires, rebind,
auto_extract)
else:
revert_mapping = (self.rebind, exec_requires, self.optional)
(self.revert_rebind, revert_requires,
self.revert_optional) = revert_mapping
self.requires = exec_requires.union(revert_requires)
def execute(self, *args, **kwargs):
return self._execute(*args, **kwargs)
def revert(self, *args, **kwargs):
if self._revert:
return self._revert(*args, **kwargs)
else:
return None
class ReduceFunctorTask(Task):
"""General purpose Task to reduce a list by applying a function.
This Task mimics the behavior of Python's built-in ``reduce`` function. The
Task takes a functor (lambda or otherwise) and a list. The list is
specified using the ``requires`` argument of the Task. When executed, this
task calls ``reduce`` with the functor and list as arguments. The resulting
value from the call to ``reduce`` is then returned after execution.
"""
def __init__(self, functor, requires, name=None, provides=None,
auto_extract=True, rebind=None, inject=None):
if not callable(functor):
raise ValueError("Function to use for reduce must be callable")
f_args = reflection.get_callable_args(functor)
if len(f_args) != 2:
raise ValueError("%s arguments were provided. Reduce functor "
"must take exactly 2 arguments." % len(f_args))
if not misc.is_iterable(requires):
raise TypeError("%s type was provided for requires. Requires "
"must be an iterable." % type(requires))
if len(requires) < 2:
raise ValueError("%s elements were provided. Requires must have "
"at least 2 elements." % len(requires))
if name is None:
name = reflection.get_callable_name(functor)
super(ReduceFunctorTask, self).__init__(name=name,
provides=provides,
inject=inject,
requires=requires,
rebind=rebind,
auto_extract=auto_extract)
self._functor = functor
def execute(self, *args, **kwargs):
l = [kwargs[r] for r in self.requires]
return functools.reduce(self._functor, l)
class MapFunctorTask(Task):
"""General purpose Task to map a function to a list.
This Task mimics the behavior of Python's built-in ``map`` function. The
Task takes a functor (lambda or otherwise) and a list. The list is
specified using the ``requires`` argument of the Task. When executed, this
task calls ``map`` with the functor and list as arguments. The resulting
list from the call to ``map`` is then returned after execution.
Each value of the returned list can be bound to individual names using
the ``provides`` argument, following taskflow standard behavior. Order is
preserved in the returned list.
"""
def __init__(self, functor, requires, name=None, provides=None,
auto_extract=True, rebind=None, inject=None):
if not callable(functor):
raise ValueError("Function to use for map must be callable")
f_args = reflection.get_callable_args(functor)
if len(f_args) != 1:
raise ValueError("%s arguments were provided. Map functor must "
"take exactly 1 argument." % len(f_args))
if not misc.is_iterable(requires):
raise TypeError("%s type was provided for requires. Requires "
"must be an iterable." % type(requires))
if name is None:
name = reflection.get_callable_name(functor)
super(MapFunctorTask, self).__init__(name=name, provides=provides,
inject=inject, requires=requires,
rebind=rebind,
auto_extract=auto_extract)
self._functor = functor
def execute(self, *args, **kwargs):
l = [kwargs[r] for r in self.requires]
return list(map(self._functor, l))