All state management moved to storage, including flow (engine) state, task states, task results and failures. Notifications for state changes were added. Storage is now implemented using taskflow.persistence and enhanced with means for result mapping and fetching task result by name. Partially implements blueprint patterns-and-engines. Co-authored-by: Anastasia Karpinska <akarpinska at griddynamics.com> Change-Id: Ia4e5707687096c948bd8db4f3d8936bdac40dd6c
142 lines
5.3 KiB
Python
142 lines
5.3 KiB
Python
# -*- coding: utf-8 -*-
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# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright (C) 2013 Rackspace Hosting Inc. All Rights Reserved.
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# Copyright (C) 2013 Yahoo! Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import abc
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from taskflow.utils import misc
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from taskflow.utils import reflection
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class BaseTask(object):
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"""An abstraction that defines a potential piece of work that can be
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applied and can be reverted to undo the work as a single unit.
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"""
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__metaclass__ = abc.ABCMeta
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def __init__(self, name):
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self._name = name
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# An *immutable* input 'resource' name set this task depends
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# on existing before this task can be applied.
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self.requires = set()
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# An *immutable* input 'resource' name set this task would like to
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# depends on existing before this task can be applied (but does not
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# strongly depend on existing).
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self.optional = set()
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# An *immutable* output 'resource' name set this task
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# produces that other tasks may depend on this task providing.
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self.provides = set()
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# This identifies the version of the task to be ran which
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# can be useful in resuming older versions of tasks. Standard
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# major, minor version semantics apply.
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self.version = (1, 0)
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@property
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def name(self):
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return self._name
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def __str__(self):
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return "%s==%s" % (self.name, misc.get_task_version(self))
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@abc.abstractmethod
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def execute(self, *args, **kwargs):
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"""Activate a given task which will perform some operation and return.
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This method can be used to apply some given context and given set
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of args and kwargs to accomplish some goal. Note that the result
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that is returned needs to be serializable so that it can be passed
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back into this task if reverting is triggered.
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"""
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def revert(self, *args, **kwargs):
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"""Revert this task using the given context, result that the apply
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provided as well as any information which may have caused
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said reversion.
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"""
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class Task(BaseTask):
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"""Base class for user-defined tasks
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Adds following features to Task:
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- auto-generates name from type of self
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- adds all execute argument names to task requiremets
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"""
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def __init__(self, name=None, requires_from_args=True):
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"""Initialize task instance
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:param name: task name, if None (the default) name will
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be autogenerated
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:param requires_from_args: if True (the default) execute
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arguments names will be added to task requirements
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"""
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if name is None:
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name = reflection.get_callable_name(self)
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super(Task, self).__init__(name)
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if requires_from_args:
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f_args = reflection.get_required_callable_args(self.execute)
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self.requires.update(a for a in f_args if a != 'context')
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class FunctorTask(BaseTask):
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"""Adaptor to make task from a callable
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Take any callable and make a task from it.
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"""
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def __init__(self, execute, **kwargs):
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"""Initialize FunctorTask instance with given callable and kwargs
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:param execute: the callable
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:param kwargs: reserved keywords (all optional) are
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name: name of the task, default None (auto generate)
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revert: the callable to revert, default None
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version: version of the task, default Task's version 1.0
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optionals: optionals of the task, default ()
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provides: provides of the task, default ()
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requires: requires of the task, default ()
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auto_extract: auto extract execute's args and put it into
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requires, default True
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"""
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name = kwargs.pop('name', None)
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if name is None:
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name = reflection.get_callable_name(execute)
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super(FunctorTask, self).__init__(name)
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self._execute = execute
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self._revert = kwargs.pop('revert', None)
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self.version = kwargs.pop('version', self.version)
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self.optional.update(kwargs.pop('optional', ()))
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self.provides.update(kwargs.pop('provides', ()))
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self.requires.update(kwargs.pop('requires', ()))
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if kwargs.pop('auto_extract', True):
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f_args = reflection.get_required_callable_args(execute)
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self.requires.update(a for a in f_args if a != 'context')
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if kwargs:
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raise TypeError('__init__() got an unexpected keyword argument %r'
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% kwargs.keys[0])
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def execute(self, *args, **kwargs):
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return self._execute(*args, **kwargs)
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def revert(self, *args, **kwargs):
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if self._revert:
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return self._revert(*args, **kwargs)
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else:
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return None
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