Files
deb-python-taskflow/taskflow/storage.py
Joshua Harlow c558da07b6 Upgrade hacking version and fix some of the issues
Update hacking to the new requirements version and
fix about half of the new reported issues. The other
hacking issues are for now ignored until fixed by
adjusting our tox.ini file.

This commit fixes the following new hacking errors:

H405 - multi line docstring summary not separated
       with an empty line
E265 - block comment should start with '# '
F402 - import 'endpoint' from line 21 shadowed by
       loop variable

Change-Id: I6bae61591fb988cc17fa79e21cb5f1508d22781c
2014-06-13 19:27:17 -07:00

595 lines
24 KiB
Python

# -*- coding: utf-8 -*-
# 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 contextlib
import logging
import six
from taskflow import exceptions
from taskflow.openstack.common import uuidutils
from taskflow.persistence import logbook
from taskflow import states
from taskflow.utils import lock_utils
from taskflow.utils import misc
from taskflow.utils import reflection
LOG = logging.getLogger(__name__)
STATES_WITH_RESULTS = (states.SUCCESS, states.REVERTING, states.FAILURE)
@six.add_metaclass(abc.ABCMeta)
class Storage(object):
"""Interface between engines and logbook.
This class provides a simple interface to save atoms of a given flow and
associated activity and results to persistence layer (logbook,
atom_details, flow_details) for use by engines. This makes it easier to
interact with the underlying storage & backend mechanism through this
interface rather than accessing those objects directly.
"""
injector_name = '_TaskFlow_INJECTOR'
def __init__(self, flow_detail, backend=None):
self._result_mappings = {}
self._reverse_mapping = {}
self._backend = backend
self._flowdetail = flow_detail
self._lock = self._lock_cls()
self._transients = {}
self._injected_args = {}
# NOTE(imelnikov): failure serialization looses information,
# so we cache failures here, in atom name -> failure mapping.
self._failures = {}
for ad in self._flowdetail:
if ad.failure is not None:
self._failures[ad.name] = ad.failure
self._atom_name_to_uuid = dict((ad.name, ad.uuid)
for ad in self._flowdetail)
try:
injector_td = self._atomdetail_by_name(
self.injector_name,
expected_type=logbook.TaskDetail)
except exceptions.NotFound:
pass
else:
names = six.iterkeys(injector_td.results)
self._set_result_mapping(injector_td.name,
dict((name, name) for name in names))
@abc.abstractproperty
def _lock_cls(self):
"""Lock class used to generate reader/writer locks.
These locks are used for protecting read/write access to the
underlying storage backend when internally mutating operations occur.
They ensure that we read and write data in a consistent manner when
being used in a multithreaded situation.
"""
def _with_connection(self, functor, *args, **kwargs):
# NOTE(harlowja): Activate the given function with a backend
# connection, if a backend is provided in the first place, otherwise
# don't call the function.
if self._backend is None:
return
with contextlib.closing(self._backend.get_connection()) as conn:
functor(conn, *args, **kwargs)
def ensure_task(self, task_name, task_version=None, result_mapping=None):
"""Ensure that there is taskdetail that corresponds the task.
If task does not exist, adds a record for it. Added task will have
PENDING state. Sets result mapping for the task from result_mapping
argument.
Returns uuid for the task details corresponding to the task with
given name.
"""
if not task_name:
raise ValueError("Task name must be non-empty")
with self._lock.write_lock():
try:
task_id = self._atom_name_to_uuid[task_name]
except KeyError:
task_id = uuidutils.generate_uuid()
self._create_atom_detail(logbook.TaskDetail, task_name,
task_id, task_version)
else:
ad = self._flowdetail.find(task_id)
if not isinstance(ad, logbook.TaskDetail):
raise exceptions.Duplicate(
"Atom detail %s already exists in flow detail %s." %
(task_name, self._flowdetail.name))
self._set_result_mapping(task_name, result_mapping)
return task_id
def ensure_retry(self, retry_name, retry_version=None,
result_mapping=None):
"""Ensure that there is atom detail that corresponds the retry.
If retry does not exist, adds a record for it. Added retry
will have PENDING state. Sets result mapping for the retry from
result_mapping argument. Initializes retry result as an empty
collections of results and failures history.
Returns uuid for the retry details corresponding to the retry
with given name.
"""
if not retry_name:
raise ValueError("Retry name must be non-empty")
with self._lock.write_lock():
try:
retry_id = self._atom_name_to_uuid[retry_name]
except KeyError:
retry_id = uuidutils.generate_uuid()
self._create_atom_detail(logbook.RetryDetail, retry_name,
retry_id, retry_version)
else:
ad = self._flowdetail.find(retry_id)
if not isinstance(ad, logbook.RetryDetail):
raise exceptions.Duplicate(
"Atom detail %s already exists in flow detail %s." %
(retry_name, self._flowdetail.name))
self._set_result_mapping(retry_name, result_mapping)
return retry_id
def _create_atom_detail(self, _detail_cls, name, uuid, task_version=None):
"""Add the atom detail to flow detail.
Atom becomes known to storage by that name and uuid.
Atom state is set to PENDING.
"""
ad = _detail_cls(name, uuid)
ad.state = states.PENDING
ad.version = task_version
self._flowdetail.add(ad)
self._with_connection(self._save_flow_detail)
self._atom_name_to_uuid[ad.name] = ad.uuid
@property
def flow_name(self):
# This never changes (so no read locking needed).
return self._flowdetail.name
@property
def flow_uuid(self):
# This never changes (so no read locking needed).
return self._flowdetail.uuid
def _save_flow_detail(self, conn):
# NOTE(harlowja): we need to update our contained flow detail if
# the result of the update actually added more (aka another process
# added item to the flow detail).
self._flowdetail.update(conn.update_flow_details(self._flowdetail))
def _atomdetail_by_name(self, atom_name, expected_type=None):
try:
ad = self._flowdetail.find(self._atom_name_to_uuid[atom_name])
except KeyError:
raise exceptions.NotFound("Unknown atom name: %s" % atom_name)
else:
# TODO(harlowja): we need to figure out how to get away from doing
# these kinds of type checks in general (since they likely mean
# we aren't doing something right).
if expected_type and not isinstance(ad, expected_type):
raise TypeError("Atom %s is not of the expected type: %s"
% (atom_name,
reflection.get_class_name(expected_type)))
return ad
def _save_atom_detail(self, conn, atom_detail):
# NOTE(harlowja): we need to update our contained atom detail if
# the result of the update actually added more (aka another process
# is also modifying the task detail), since python is by reference
# and the contained atom detail will reflect the old state if we don't
# do this update.
atom_detail.update(conn.update_atom_details(atom_detail))
def get_atom_uuid(self, atom_name):
"""Gets an atoms uuid given a atoms name."""
with self._lock.read_lock():
ad = self._atomdetail_by_name(atom_name)
return ad.uuid
def set_atom_state(self, atom_name, state):
"""Sets an atoms state."""
with self._lock.write_lock():
ad = self._atomdetail_by_name(atom_name)
ad.state = state
self._with_connection(self._save_atom_detail, ad)
def get_atom_state(self, atom_name):
"""Gets the state of an atom given an atoms name."""
with self._lock.read_lock():
ad = self._atomdetail_by_name(atom_name)
return ad.state
def set_atom_intention(self, atom_name, intention):
"""Sets the intention of an atom given an atoms name."""
ad = self._atomdetail_by_name(atom_name)
ad.intention = intention
self._with_connection(self._save_atom_detail, ad)
def get_atom_intention(self, atom_name):
"""Gets the intention of an atom given an atoms name."""
ad = self._atomdetail_by_name(atom_name)
return ad.intention
def get_atoms_states(self, atom_names):
"""Gets all atoms states given a set of names."""
with self._lock.read_lock():
return dict((name, (self.get_atom_state(name),
self.get_atom_intention(name)))
for name in atom_names)
def _update_atom_metadata(self, atom_name, update_with,
expected_type=None):
with self._lock.write_lock():
ad = self._atomdetail_by_name(atom_name,
expected_type=expected_type)
if update_with:
ad.meta.update(update_with)
self._with_connection(self._save_atom_detail, ad)
def update_atom_metadata(self, atom_name, update_with):
"""Updates a atoms associated metadata.
This update will take a provided dictionary or a list of (key, value)
pairs to include in the updated metadata (newer keys will overwrite
older keys) and after merging saves the updated data into the
underlying persistence layer.
"""
self._update_atom_metadata(atom_name, update_with)
def set_task_progress(self, task_name, progress, details=None):
"""Set a tasks progress.
:param task_name: task name
:param progress: tasks progress (0.0 <-> 1.0)
:param details: any task specific progress details
"""
update_with = {
'progress': progress,
}
if details is not None:
# NOTE(imelnikov): as we can update progress without
# updating details (e.g. automatically from engine)
# we save progress value with details, too.
if details:
update_with['progress_details'] = {
'at_progress': progress,
'details': details,
}
else:
update_with['progress_details'] = None
self._update_atom_metadata(task_name, update_with,
expected_type=logbook.TaskDetail)
def get_task_progress(self, task_name):
"""Get the progress of a task given a tasks name.
:param task_name: tasks name
:returns: current task progress value
"""
with self._lock.read_lock():
ad = self._atomdetail_by_name(task_name,
expected_type=logbook.TaskDetail)
try:
return ad.meta['progress']
except KeyError:
return 0.0
def get_task_progress_details(self, task_name):
"""Get the progress details of a task given a tasks name.
:param task_name: task name
:returns: None if progress_details not defined, else progress_details
dict
"""
with self._lock.read_lock():
ad = self._atomdetail_by_name(task_name,
expected_type=logbook.TaskDetail)
try:
return ad.meta['progress_details']
except KeyError:
return None
def _check_all_results_provided(self, atom_name, data):
"""Warn if an atom did not provide some of its expected results.
This may happen if atom returns shorter tuple or list or dict
without all needed keys. It may also happen if atom returns
result of wrong type.
"""
result_mapping = self._result_mappings.get(atom_name)
if not result_mapping:
return
for name, index in six.iteritems(result_mapping):
try:
misc.item_from(data, index, name=name)
except exceptions.NotFound:
LOG.warning("Atom %s did not supply result "
"with index %r (name %s)", atom_name, index, name)
def save(self, atom_name, data, state=states.SUCCESS):
"""Put result for atom with id 'uuid' to storage."""
with self._lock.write_lock():
ad = self._atomdetail_by_name(atom_name)
ad.put(state, data)
if state == states.FAILURE and isinstance(data, misc.Failure):
# NOTE(imelnikov): failure serialization looses information,
# so we cache failures here, in atom name -> failure mapping.
self._failures[ad.name] = data
else:
self._check_all_results_provided(ad.name, data)
self._with_connection(self._save_atom_detail, ad)
def save_retry_failure(self, retry_name, failed_atom_name, failure):
"""Save subflow failure to retry controller history."""
with self._lock.write_lock():
ad = self._atomdetail_by_name(retry_name,
expected_type=logbook.RetryDetail)
try:
failures = ad.last_failures
except exceptions.NotFound as e:
raise exceptions.StorageFailure("Unable to fetch most recent"
" retry failures so new retry"
" failure can be inserted", e)
else:
if failed_atom_name not in failures:
failures[failed_atom_name] = failure
self._with_connection(self._save_atom_detail, ad)
def cleanup_retry_history(self, retry_name, state):
"""Cleanup history of retry atom with given name."""
with self._lock.write_lock():
ad = self._atomdetail_by_name(retry_name,
expected_type=logbook.RetryDetail)
ad.state = state
ad.results = []
self._with_connection(self._save_atom_detail, ad)
def _get(self, atom_name, only_last=False):
with self._lock.read_lock():
ad = self._atomdetail_by_name(atom_name)
if ad.failure is not None:
cached = self._failures.get(atom_name)
if ad.failure.matches(cached):
return cached
return ad.failure
if ad.state not in STATES_WITH_RESULTS:
raise exceptions.NotFound("Result for atom %s is not currently"
" known" % atom_name)
if only_last:
return ad.last_results
else:
return ad.results
def get(self, atom_name):
"""Gets the results for an atom with a given name from storage."""
return self._get(atom_name)
def get_failures(self):
"""Get list of failures that happened with this flow.
No order guaranteed.
"""
with self._lock.read_lock():
return self._failures.copy()
def has_failures(self):
"""Returns True if there are failed tasks in the storage."""
with self._lock.read_lock():
return bool(self._failures)
def _reset_atom(self, ad, state):
if ad.name == self.injector_name:
return False
if ad.state == state:
return False
ad.reset(state)
self._failures.pop(ad.name, None)
return True
def reset(self, atom_name, state=states.PENDING):
"""Reset atom with given name (if the task is in a given state)."""
with self._lock.write_lock():
ad = self._atomdetail_by_name(atom_name)
if self._reset_atom(ad, state):
self._with_connection(self._save_atom_detail, ad)
def inject_atom_args(self, atom_name, pairs):
"""Add *transient* values into storage for a specific atom only.
This method injects a dictionary/pairs of arguments for an atom so that
when that atom is scheduled for execution it will have immediate access
to these arguments.
NOTE(harlowja): injected atom arguments take precedence over arguments
provided by predecessor atoms or arguments provided by injecting into
the flow scope (using the inject() method).
"""
if atom_name not in self._atom_name_to_uuid:
raise exceptions.NotFound("Unknown atom name: %s" % atom_name)
with self._lock.write_lock():
self._injected_args.setdefault(atom_name, {})
self._injected_args[atom_name].update(pairs)
def inject(self, pairs, transient=False):
"""Add values into storage.
This method should be used to put flow parameters (requirements that
are not satisfied by any task in the flow) into storage.
:param: transient save the data in-memory only instead of persisting
the data to backend storage (useful for resource-like objects
or similar objects which should *not* be persisted)
"""
def save_persistent():
try:
ad = self._atomdetail_by_name(self.injector_name,
expected_type=logbook.TaskDetail)
except exceptions.NotFound:
uuid = uuidutils.generate_uuid()
self._create_atom_detail(logbook.TaskDetail,
self.injector_name, uuid)
ad = self._atomdetail_by_name(self.injector_name,
expected_type=logbook.TaskDetail)
ad.results = dict(pairs)
ad.state = states.SUCCESS
else:
ad.results.update(pairs)
self._with_connection(self._save_atom_detail, ad)
return (self.injector_name, six.iterkeys(ad.results))
def save_transient():
self._transients.update(pairs)
# NOTE(harlowja): none is not a valid atom name, so that means
# we can use it internally to reference all of our transient
# variables.
return (None, six.iterkeys(self._transients))
with self._lock.write_lock():
if transient:
(atom_name, names) = save_transient()
else:
(atom_name, names) = save_persistent()
self._set_result_mapping(atom_name,
dict((name, name) for name in names))
def _set_result_mapping(self, atom_name, mapping):
"""Sets the result mapping for an atom.
The result saved with given name 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[atom_name] = mapping
for name, index in six.iteritems(mapping):
entries = self._reverse_mapping.setdefault(name, [])
# NOTE(imelnikov): We support setting same result mapping for
# the same atom twice (e.g when we are injecting 'a' and then
# injecting 'a' again), so we should not log warning below in
# that case and we should have only one item for each pair
# (atom_name, index) in entries. It should be put to the end of
# entries list because order matters on fetching.
try:
entries.remove((atom_name, index))
except ValueError:
pass
entries.append((atom_name, index))
if len(entries) > 1:
LOG.warning("Multiple provider mappings being created for %r",
name)
def fetch(self, name):
"""Fetch a named atoms result."""
with self._lock.read_lock():
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 (atom_name, index) in reversed(indexes):
if not atom_name:
results = self._transients
else:
results = self._get(atom_name, only_last=True)
try:
return misc.item_from(results, index, name)
except exceptions.NotFound:
pass
raise exceptions.NotFound("Unable to find result %r" % name)
def fetch_all(self):
"""Fetch all named atom results known so far.
Should be used for debugging and testing purposes mostly.
"""
with self._lock.read_lock():
results = {}
for name in self._reverse_mapping:
try:
results[name] = self.fetch(name)
except exceptions.NotFound:
pass
return results
def fetch_mapped_args(self, args_mapping, atom_name=None):
"""Fetch arguments for an atom using an atoms arguments mapping."""
with self._lock.read_lock():
injected_args = {}
if atom_name:
injected_args = self._injected_args.get(atom_name, {})
mapped_args = {}
for key, name in six.iteritems(args_mapping):
if name in injected_args:
mapped_args[key] = injected_args[name]
else:
mapped_args[key] = self.fetch(name)
return mapped_args
def set_flow_state(self, state):
"""Set flow details state and save it."""
with self._lock.write_lock():
self._flowdetail.state = state
self._with_connection(self._save_flow_detail)
def get_flow_state(self):
"""Get state from flow details."""
with self._lock.read_lock():
state = self._flowdetail.state
if state is None:
state = states.PENDING
return state
def get_retry_history(self, retry_name):
"""Fetch retry results history."""
with self._lock.read_lock():
ad = self._atomdetail_by_name(retry_name,
expected_type=logbook.RetryDetail)
if ad.failure is not None:
cached = self._failures.get(retry_name)
history = list(ad.results)
if ad.failure.matches(cached):
history.append((cached, {}))
else:
history.append((ad.failure, {}))
return history
return ad.results
class MultiThreadedStorage(Storage):
"""Storage that uses locks to protect against concurrent access."""
_lock_cls = lock_utils.ReaderWriterLock
class SingleThreadedStorage(Storage):
"""Storage that uses dummy locks when you really don't need locks."""
_lock_cls = lock_utils.DummyReaderWriterLock