Files
deb-python-taskflow/taskflow/storage.py
Joshua Harlow 8218f57ad2 Allow provides to be a set and results to be a dictionary
Instead of forcing task provides to be a tuple or list and
using the corresponding numerical index to determine how to
interpret the tasks results we should also allow for the task
provides to be a set and then allow for the tasks result to be
interpreted as a dictionary.

Fixes bug 1221998

Change-Id: Ibae689e7975d6782aa248d2b6e3691c44a89ef9f
2013-09-07 11:12:43 -07:00

214 lines
7.3 KiB
Python

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# 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.
from taskflow import exceptions
from taskflow.openstack.common import uuidutils
from taskflow.persistence import flowdetail
from taskflow.persistence import logbook
from taskflow.persistence import taskdetail
from taskflow import states
from taskflow.utils import threading_utils
def temporary_flow_detail():
"""Creates flow detail class for temporary usage
Creates in-memory logbook and flow detail in it. Should
be useful for tests and other use cases where persistence
is not needed
"""
lb = logbook.LogBook('tmp', backend='memory')
fd = flowdetail.FlowDetail(
name='tmp', uuid=uuidutils.generate_uuid(),
backend='memory')
lb.add(fd)
lb.save()
fd.save()
return fd
STATES_WITH_RESULTS = (states.SUCCESS, states.REVERTING, states.FAILURE)
class Storage(object):
"""Interface between engines and logbook
This class provides simple interface to save task details and
results to persistence layer for use by engines.
"""
injector_name = '_TaskFlow_INJECTOR'
def __init__(self, flow_detail=None):
self._result_mappings = {}
self._reverse_mapping = {}
if flow_detail is None:
# TODO(imelnikov): this is useful mainly for tests;
# maybe we should make flow_detail required parameter?
self._flowdetail = temporary_flow_detail()
else:
self._flowdetail = flow_detail
def add_task(self, uuid, task_name):
"""Add the task to storage
Task becomes known to storage by that name and uuid.
Task state is set to PENDING.
"""
# TODO(imelnikov): check that task with same uuid or
# task name does not exist
td = taskdetail.TaskDetail(name=task_name, uuid=uuid)
td.state = states.PENDING
self._flowdetail.add(td)
self._flowdetail.save()
td.save()
def get_uuid_by_name(self, task_name):
"""Get uuid of task with given name"""
td = self._flowdetail.find_by_name(task_name)
if td is not None:
return td.uuid
else:
raise exceptions.NotFound("Unknown task name: %r" % task_name)
def _taskdetail_by_uuid(self, uuid):
td = self._flowdetail.find(uuid)
if td is None:
raise exceptions.NotFound("Unknown task: %r" % uuid)
return td
def set_task_state(self, uuid, state):
"""Set task state"""
td = self._taskdetail_by_uuid(uuid)
td.state = state
td.save()
def get_task_state(self, uuid):
"""Get state of task with given uuid"""
return self._taskdetail_by_uuid(uuid).state
def save(self, uuid, data, state=states.SUCCESS):
"""Put result for task with id 'uuid' to storage"""
td = self._taskdetail_by_uuid(uuid)
td.state = state
td.results = data
td.save()
def get(self, uuid):
"""Get result for task with id 'uuid' to storage"""
td = self._taskdetail_by_uuid(uuid)
if td.state not in STATES_WITH_RESULTS:
raise exceptions.NotFound("Result for task %r is not known" % uuid)
return td.results
def reset(self, uuid, state=states.PENDING):
"""Remove result for task with id 'uuid' from storage"""
td = self._taskdetail_by_uuid(uuid)
td.results = None
td.state = state
td.save()
def inject(self, pairs):
"""Add values into storage
This method should be used by job in order to put flow parameters
into storage and put it to action.
"""
pairs = dict(pairs)
injector_uuid = uuidutils.generate_uuid()
self.add_task(injector_uuid, self.injector_name)
self.save(injector_uuid, pairs)
for name in pairs.iterkeys():
entries = self._reverse_mapping.setdefault(name, [])
entries.append((injector_uuid, name))
def set_result_mapping(self, uuid, mapping):
"""Set mapping for naming task results
The result saved with given uuid would be accessible by names
defined in mapping. Mapping is a dict name => index. If index
is None, the whole result will have this name; else, only
part of it, result[index].
"""
if not mapping:
return
self._result_mappings[uuid] = mapping
for name, index in mapping.iteritems():
entries = self._reverse_mapping.setdefault(name, [])
entries.append((uuid, index))
def fetch(self, name):
"""Fetch named task result"""
try:
indexes = self._reverse_mapping[name]
except KeyError:
raise exceptions.NotFound("Name %r is not mapped" % name)
# Return the first one that is found.
for uuid, index in indexes:
try:
result = self.get(uuid)
if index is None:
return result
else:
return result[index]
except exceptions.NotFound:
# NOTE(harlowja): No result was found for the given uuid.
pass
except (KeyError, IndexError, TypeError):
# NOTE(harlowja): The result that the uuid returned can not be
# accessed in the manner that the index is requesting. Perhaps
# the result is a dictionary-like object and that key does
# not exist (key error), or the result is a tuple/list and a
# non-numeric key is being requested (index error), or there
# was no result and an attempt to index into None is being
# requested (type error).
pass
raise exceptions.NotFound("Unable to find result %r" % name)
def fetch_all(self):
"""Fetch all named task results known so far
Should be used for debugging and testing purposes mostly.
"""
result = {}
for name in self._reverse_mapping:
try:
result[name] = self.fetch(name)
except exceptions.NotFound:
pass
return result
def fetch_mapped_args(self, args_mapping):
"""Fetch arguments for the task using arguments mapping"""
return dict((key, self.fetch(name))
for key, name in args_mapping.iteritems())
def set_flow_state(self, state):
"""Set flowdetails state and save it"""
self._flowdetail.state = state
self._flowdetail.save()
def get_flow_state(self):
"""Set state from flowdetails"""
return self._flowdetail.state
class ThreadSafeStorage(Storage):
__metaclass__ = threading_utils.ThreadSafeMeta