openstack/deb-python-taskflow
Code Issues Proposed changes
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d5e43e3dc37ccdca2e33aa364776430de4877e65
deb-python-taskflow/taskflow/storage.py
Joshua Harlow a0ca0af79f Refactor common parts of 'get_maybe_ready_for' methods 
These share quite a bit of common-like code, so refactor
both of them to share the same function and differentiate
certain provided arguments as needed.

Also tweaks the storage class 'get_atoms_states' (which
is badly named also) to not do two queries into the flow
detail when one will suffice and to not request the same
atom name twice when once will suffice.

Change-Id: Ifdf2f3efb78d189ed5a8104614b1bf6a84c9339a
2015-09-22 12:41:23 -07:00

1066 lines
45 KiB
Python
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# -*- 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 contextlib
import fasteners
from oslo_utils import reflection
from oslo_utils import uuidutils
import six
from taskflow import exceptions
from taskflow import logging
from taskflow.persistence.backends import impl_memory
from taskflow.persistence import models
from taskflow import retry
from taskflow import states
from taskflow import task
from taskflow.utils import misc
LOG = logging.getLogger(__name__)
_EXECUTE_STATES_WITH_RESULTS = (
# The atom ``execute`` worked out :)
states.SUCCESS,
# The atom ``execute`` didn't work out :(
states.FAILURE,
# In this state we will still have access to prior SUCCESS (or FAILURE)
# results, so make sure extraction is still allowed in this state...
states.REVERTING,
)
_REVERT_STATES_WITH_RESULTS = (
# The atom ``revert`` worked out :)
states.REVERTED,
# The atom ``revert`` didn't work out :(
states.REVERT_FAILURE,
# In this state we will still have access to prior SUCCESS (or FAILURE)
# results, so make sure extraction is still allowed in this state...
states.REVERTING,
)
# Atom states that may have results...
STATES_WITH_RESULTS = set()
STATES_WITH_RESULTS.update(_REVERT_STATES_WITH_RESULTS)
STATES_WITH_RESULTS.update(_EXECUTE_STATES_WITH_RESULTS)
STATES_WITH_RESULTS = tuple(sorted(STATES_WITH_RESULTS))
# TODO(harlowja): do this better (via a singleton or something else...)
_TRANSIENT_PROVIDER = object()
# Only for these intentions will we cache any failures that happened...
_SAVE_FAILURE_INTENTIONS = (states.EXECUTE, states.REVERT)
# NOTE(harlowja): Perhaps the container is a dictionary-like object and that
# key does not exist (key error), or the container is a tuple/list and a
# non-numeric key is being requested (index error), or there was no container
# and an attempt to index into none/other unsubscriptable type is being
# requested (type error).
#
# Overall this (along with the item_from* functions) try to handle the vast
# majority of wrong indexing operations on the wrong/invalid types so that we
# can fail extraction during lookup or emit warning on result reception...
_EXTRACTION_EXCEPTIONS = (IndexError, KeyError, ValueError, TypeError)
# Atom detail metadata key used to inject atom non-transient injected args.
META_INJECTED = 'injected'
# Atom detail metadata key(s) used to set atom progress (with any details).
META_PROGRESS = 'progress'
META_PROGRESS_DETAILS = 'progress_details'
class _Provider(object):
"""A named symbol provider that produces a output at the given index."""
def __init__(self, name, index):
self.name = name
self.index = index
def __repr__(self):
# TODO(harlowja): clean this up...
if self.name is _TRANSIENT_PROVIDER:
base = "<TransientProvider"
else:
base = "<Provider '%s'" % (self.name)
if self.index is None:
base += ">"
else:
base += " @ index %r>" % (self.index)
return base
def __hash__(self):
return hash((self.name, self.index))
def __eq__(self, other):
return (self.name, self.index) == (other.name, other.index)
def _item_from(container, index):
"""Attempts to fetch a index/key from a given container."""
if index is None:
return container
return container[index]
def _item_from_single(provider, container, looking_for):
"""Returns item from a *single* provider."""
try:
return _item_from(container, provider.index)
except _EXTRACTION_EXCEPTIONS:
exceptions.raise_with_cause(
exceptions.NotFound,
"Unable to find result %r, expected to be able to find it"
" created by %s but was unable to perform successful"
" extraction" % (looking_for, provider))
def _item_from_first_of(providers, looking_for):
"""Returns item from the *first* successful container extraction."""
for (provider, container) in providers:
try:
return (provider, _item_from(container, provider.index))
except _EXTRACTION_EXCEPTIONS:
pass
providers = [p[0] for p in providers]
raise exceptions.NotFound(
"Unable to find result %r, expected to be able to find it"
" created by one of %s but was unable to perform successful"
" extraction" % (looking_for, providers))
class Storage(object):
"""Interface between engines and logbook and its backend (if any).
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.
NOTE(harlowja): if no backend is provided then a in-memory backend will
be automatically used and the provided flow detail object will be placed
into it for the duration of this objects existence.
"""
injector_name = '_TaskFlow_INJECTOR'
"""Injector task detail name.
This task detail is a **special** detail that will be automatically
created and saved to store **persistent** injected values (name conflicts
with it must be avoided) that are *global* to the flow being executed.
"""
def __init__(self, flow_detail, backend=None, scope_fetcher=None):
self._result_mappings = {}
self._reverse_mapping = {}
if backend is None:
# Err on the likely-hood that most people don't make there
# objects able to be deepcopyable (resources, locks and such
# can't be deepcopied)...
backend = impl_memory.MemoryBackend({'deep_copy': False})
with contextlib.closing(backend.get_connection()) as conn:
conn.update_flow_details(flow_detail, ignore_missing=True)
self._backend = backend
self._flowdetail = flow_detail
self._transients = {}
self._injected_args = {}
self._lock = fasteners.ReaderWriterLock()
self._ensure_matchers = [
((task.BaseTask,), (models.TaskDetail, 'Task')),
((retry.Retry,), (models.RetryDetail, 'Retry')),
]
if scope_fetcher is None:
scope_fetcher = lambda atom_name: None
self._scope_fetcher = scope_fetcher
# NOTE(imelnikov): failure serialization looses information,
# so we cache failures here, in atom name -> failure mapping.
self._failures = {}
for ad in self._flowdetail:
fail_cache = {}
if ad.failure is not None:
fail_cache[states.EXECUTE] = ad.failure
if ad.revert_failure is not None:
fail_cache[states.REVERT] = ad.revert_failure
self._failures[ad.name] = fail_cache
self._atom_name_to_uuid = dict((ad.name, ad.uuid)
for ad in self._flowdetail)
try:
source, _clone = self._atomdetail_by_name(
self.injector_name, expected_type=models.TaskDetail)
except exceptions.NotFound:
pass
else:
names_iter = six.iterkeys(source.results)
self._set_result_mapping(source.name,
dict((name, name) for name in names_iter))
def _with_connection(self, functor, *args, **kwargs):
# Run the given functor with a backend connection as its first
# argument (providing the additional positional arguments and keyword
# arguments as subsequent arguments).
with contextlib.closing(self._backend.get_connection()) as conn:
return functor(conn, *args, **kwargs)
@staticmethod
def _create_atom_detail(atom_name, atom_detail_cls,
atom_version=None, atom_state=states.PENDING):
ad = atom_detail_cls(atom_name, uuidutils.generate_uuid())
ad.state = atom_state
if atom_version is not None:
ad.version = atom_version
return ad
@fasteners.write_locked
def ensure_atoms(self, atoms):
"""Ensure there is an atomdetail for **each** of the given atoms.
Returns list of atomdetail uuids for each atom processed.
"""
atom_ids = []
missing_ads = []
for i, atom in enumerate(atoms):
match = misc.match_type(atom, self._ensure_matchers)
if not match:
raise TypeError("Unknown atom '%s' (%s) requested to ensure"
% (atom, type(atom)))
atom_detail_cls, kind = match
atom_name = atom.name
if not atom_name:
raise ValueError("%s name must be non-empty" % (kind))
try:
atom_id = self._atom_name_to_uuid[atom_name]
except KeyError:
missing_ads.append((i, atom, atom_detail_cls))
# This will be later replaced with the uuid that is created...
atom_ids.append(None)
else:
ad = self._flowdetail.find(atom_id)
if not isinstance(ad, atom_detail_cls):
raise exceptions.Duplicate(
"Atom detail '%s' already exists in flow"
" detail '%s'" % (atom_name, self._flowdetail.name))
else:
atom_ids.append(ad.uuid)
self._set_result_mapping(atom_name, atom.save_as)
if missing_ads:
needs_to_be_created_ads = []
for (i, atom, atom_detail_cls) in missing_ads:
ad = self._create_atom_detail(
atom.name, atom_detail_cls,
atom_version=misc.get_version_string(atom))
needs_to_be_created_ads.append((i, atom, ad))
# Add the atom detail(s) to a clone, which upon success will be
# updated into the contained flow detail; if it does not get saved
# then no update will happen.
source, clone = self._fetch_flowdetail(clone=True)
for (_i, _atom, ad) in needs_to_be_created_ads:
clone.add(ad)
self._with_connection(self._save_flow_detail, source, clone)
# Insert the needed data, and get outta here...
for (i, atom, ad) in needs_to_be_created_ads:
atom_name = atom.name
atom_ids[i] = ad.uuid
self._atom_name_to_uuid[atom_name] = ad.uuid
self._set_result_mapping(atom_name, atom.save_as)
self._failures.setdefault(atom_name, {})
return atom_ids
def ensure_atom(self, atom):
"""Ensure there is an atomdetail for the **given** atom.
Returns the uuid for the atomdetail that corresponds to the given atom.
"""
return self.ensure_atoms([atom])[0]
@property
def flow_name(self):
"""The flow detail name this storage unit is associated with."""
# This never changes (so no read locking needed).
return self._flowdetail.name
@property
def flow_uuid(self):
"""The flow detail uuid this storage unit is associated with."""
# This never changes (so no read locking needed).
return self._flowdetail.uuid
@property
def backend(self):
"""The backend this storage unit is associated with."""
# This never changes (so no read locking needed).
return self._backend
def _save_flow_detail(self, conn, original_flow_detail, flow_detail):
# 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).
original_flow_detail.update(conn.update_flow_details(flow_detail))
return original_flow_detail
def _fetch_flowdetail(self, clone=False):
source = self._flowdetail
if clone:
return (source, source.copy())
else:
return (source, source)
def _atomdetail_by_name(self, atom_name, expected_type=None, clone=False):
try:
ad = self._flowdetail.find(self._atom_name_to_uuid[atom_name])
except KeyError:
exceptions.raise_with_cause(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)))
if clone:
return (ad, ad.copy())
else:
return (ad, ad)
def _save_atom_detail(self, conn, original_atom_detail, 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.
original_atom_detail.update(conn.update_atom_details(atom_detail))
return original_atom_detail
@fasteners.read_locked
def get_atom_uuid(self, atom_name):
"""Gets an atoms uuid given a atoms name."""
source, _clone = self._atomdetail_by_name(atom_name)
return source.uuid
@fasteners.write_locked
def set_atom_state(self, atom_name, state):
"""Sets an atoms state."""
source, clone = self._atomdetail_by_name(atom_name, clone=True)
if source.state != state:
clone.state = state
self._with_connection(self._save_atom_detail, source, clone)
@fasteners.read_locked
def get_atom_state(self, atom_name):
"""Gets the state of an atom given an atoms name."""
source, _clone = self._atomdetail_by_name(atom_name)
return source.state
@fasteners.write_locked
def set_atom_intention(self, atom_name, intention):
"""Sets the intention of an atom given an atoms name."""
source, clone = self._atomdetail_by_name(atom_name, clone=True)
if source.intention != intention:
clone.intention = intention
self._with_connection(self._save_atom_detail, source, clone)
@fasteners.read_locked
def get_atom_intention(self, atom_name):
"""Gets the intention of an atom given an atoms name."""
source, _clone = self._atomdetail_by_name(atom_name)
return source.intention
@fasteners.read_locked
def get_atoms_states(self, atom_names):
"""Gets a dict of atom name => (state, intention) given atom names."""
details = {}
for name in set(atom_names):
source, _clone = self._atomdetail_by_name(name)
details[name] = (source.state, source.intention)
return details
@fasteners.write_locked
def _update_atom_metadata(self, atom_name, update_with,
expected_type=None):
source, clone = self._atomdetail_by_name(atom_name,
expected_type=expected_type,
clone=True)
if update_with:
clone.meta.update(update_with)
self._with_connection(self._save_atom_detail, source, clone)
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 = {
META_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[META_PROGRESS_DETAILS] = {
'at_progress': progress,
'details': details,
}
else:
update_with[META_PROGRESS_DETAILS] = None
self._update_atom_metadata(task_name, update_with,
expected_type=models.TaskDetail)
@fasteners.read_locked
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
"""
source, _clone = self._atomdetail_by_name(
task_name, expected_type=models.TaskDetail)
try:
return source.meta[META_PROGRESS]
except KeyError:
return 0.0
@fasteners.read_locked
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
"""
source, _clone = self._atomdetail_by_name(
task_name, expected_type=models.TaskDetail)
try:
return source.meta[META_PROGRESS_DETAILS]
except KeyError:
return None
def _check_all_results_provided(self, atom_name, container):
"""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:
_item_from(container, index)
except _EXTRACTION_EXCEPTIONS:
LOG.warning("Atom %s did not supply result "
"with index %r (name %s)", atom_name, index, name)
@fasteners.write_locked
def save(self, atom_name, result, state=states.SUCCESS):
"""Put result for atom with provided name to storage."""
source, clone = self._atomdetail_by_name(atom_name, clone=True)
if clone.put(state, result):
self._with_connection(self._save_atom_detail, source, clone)
# We need to somehow place more of this responsibility on the atom
# detail class itself, vs doing it here; since it ties those two
# together (which is bad)...
if state in (states.FAILURE, states.REVERT_FAILURE):
# NOTE(imelnikov): failure serialization looses information,
# so we cache failures here, in atom name -> failure mapping so
# that we can later use the better version on fetch/get.
if clone.intention in _SAVE_FAILURE_INTENTIONS:
fail_cache = self._failures[clone.name]
fail_cache[clone.intention] = result
if state == states.SUCCESS and clone.intention == states.EXECUTE:
self._check_all_results_provided(clone.name, result)
@fasteners.write_locked
def save_retry_failure(self, retry_name, failed_atom_name, failure):
"""Save subflow failure to retry controller history."""
source, clone = self._atomdetail_by_name(
retry_name, expected_type=models.RetryDetail, clone=True)
try:
failures = clone.last_failures
except exceptions.NotFound:
exceptions.raise_with_cause(exceptions.StorageFailure,
"Unable to fetch most recent retry"
" failures so new retry failure can"
" be inserted")
else:
if failed_atom_name not in failures:
failures[failed_atom_name] = failure
self._with_connection(self._save_atom_detail, source, clone)
@fasteners.write_locked
def cleanup_retry_history(self, retry_name, state):
"""Cleanup history of retry atom with given name."""
source, clone = self._atomdetail_by_name(
retry_name, expected_type=models.RetryDetail, clone=True)
clone.state = state
clone.results = []
self._with_connection(self._save_atom_detail, source, clone)
@fasteners.read_locked
def _get(self, atom_name,
results_attr_name, fail_attr_name,
allowed_states, fail_cache_key):
source, _clone = self._atomdetail_by_name(atom_name)
failure = getattr(source, fail_attr_name)
if failure is not None:
fail_cache = self._failures[atom_name]
try:
fail = fail_cache[fail_cache_key]
if failure.matches(fail):
# Try to give the version back that should have the
# backtrace instead of one that has it
# stripped (since backtraces are not serializable).
failure = fail
except KeyError:
pass
return failure
# TODO(harlowja): this seems like it should be checked before fetching
# the potential failure, instead of after, fix this soon...
if source.state not in allowed_states:
raise exceptions.NotFound("Result for atom %s is not currently"
" known" % atom_name)
return getattr(source, results_attr_name)
def get_execute_result(self, atom_name):
"""Gets the ``execute`` results for an atom from storage."""
return self._get(atom_name, 'results', 'failure',
_EXECUTE_STATES_WITH_RESULTS, states.EXECUTE)
@fasteners.read_locked
def _get_failures(self, fail_cache_key):
failures = {}
for atom_name, fail_cache in six.iteritems(self._failures):
try:
failures[atom_name] = fail_cache[fail_cache_key]
except KeyError:
pass
return failures
def get_execute_failures(self):
"""Get all ``execute`` failures that happened with this flow."""
return self._get_failures(states.EXECUTE)
# TODO(harlowja): remove these in the future?
get = get_execute_result
get_failures = get_execute_failures
def get_revert_result(self, atom_name):
"""Gets the ``revert`` results for an atom from storage."""
return self._get(atom_name, 'revert_results', 'revert_failure',
_REVERT_STATES_WITH_RESULTS, states.REVERT)
def get_revert_failures(self):
"""Get all ``revert`` failures that happened with this flow."""
return self._get_failures(states.REVERT)
@fasteners.read_locked
def has_failures(self):
"""Returns true if there are **any** failures in storage."""
for fail_cache in six.itervalues(self._failures):
if fail_cache:
return True
return False
@fasteners.write_locked
def reset(self, atom_name, state=states.PENDING):
"""Reset atom with given name (if the atom is not in a given state)."""
if atom_name == self.injector_name:
return
source, clone = self._atomdetail_by_name(atom_name, clone=True)
if source.state == state:
return
clone.reset(state)
self._with_connection(self._save_atom_detail, source, clone)
self._failures[clone.name].clear()
def inject_atom_args(self, atom_name, pairs, transient=True):
"""Add values into storage for a specific atom only.
: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 can **not** be persisted)
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::
Injected atom arguments take precedence over arguments
provided by predecessor atoms or arguments provided by injecting
into the flow scope (using
the :py:meth:`~taskflow.storage.Storage.inject` method).
.. warning::
It should be noted that injected atom arguments (that are scoped
to the atom with the given name) *should* be serializable
whenever possible. This is a **requirement** for the
:doc:`worker based engine <workers>` which **must**
serialize (typically using ``json``) all
atom :py:meth:`~taskflow.atom.Atom.execute` and
:py:meth:`~taskflow.atom.Atom.revert` arguments to
be able to transmit those arguments to the target worker(s). If
the use-case being applied/desired is to later use the worker
based engine then it is highly recommended to ensure all injected
atoms (even transient ones) are serializable to avoid issues
that *may* appear later (when a object turned out to not actually
be serializable).
"""
if atom_name not in self._atom_name_to_uuid:
raise exceptions.NotFound("Unknown atom name: %s" % atom_name)
def save_transient():
self._injected_args.setdefault(atom_name, {})
self._injected_args[atom_name].update(pairs)
def save_persistent():
source, clone = self._atomdetail_by_name(atom_name, clone=True)
injected = source.meta.get(META_INJECTED)
if not injected:
injected = {}
injected.update(pairs)
clone.meta[META_INJECTED] = injected
self._with_connection(self._save_atom_detail, source, clone)
with self._lock.write_lock():
if transient:
save_transient()
else:
save_persistent()
@fasteners.write_locked
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 atom 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 can **not** be persisted)
.. warning::
It should be noted that injected flow arguments (that are scoped
to all atoms in this flow) *should* be serializable whenever
possible. This is a **requirement** for
the :doc:`worker based engine <workers>` which **must**
serialize (typically using ``json``) all
atom :py:meth:`~taskflow.atom.Atom.execute` and
:py:meth:`~taskflow.atom.Atom.revert` arguments to
be able to transmit those arguments to the target worker(s). If
the use-case being applied/desired is to later use the worker
based engine then it is highly recommended to ensure all injected
atoms (even transient ones) are serializable to avoid issues
that *may* appear later (when a object turned out to not actually
be serializable).
"""
def save_persistent():
try:
source, clone = self._atomdetail_by_name(
self.injector_name,
expected_type=models.TaskDetail,
clone=True)
except exceptions.NotFound:
# Ensure we have our special task detail...
#
# TODO(harlowja): get this removed when
# https://review.openstack.org/#/c/165645/ merges.
source = self._create_atom_detail(self.injector_name,
models.TaskDetail,
atom_state=None)
fd_source, fd_clone = self._fetch_flowdetail(clone=True)
fd_clone.add(source)
self._with_connection(self._save_flow_detail, fd_source,
fd_clone)
self._atom_name_to_uuid[source.name] = source.uuid
clone = source
clone.results = dict(pairs)
clone.state = states.SUCCESS
else:
clone.results.update(pairs)
result = self._with_connection(self._save_atom_detail,
source, clone)
return (self.injector_name, six.iterkeys(result.results))
def save_transient():
self._transients.update(pairs)
return (_TRANSIENT_PROVIDER, six.iterkeys(self._transients))
if transient:
provider_name, names = save_transient()
else:
provider_name, names = save_persistent()
self._set_result_mapping(provider_name,
dict((name, name) for name in names))
def _set_result_mapping(self, provider_name, mapping):
"""Sets the result mapping for a given producer.
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].
"""
provider_mapping = self._result_mappings.setdefault(provider_name, {})
if mapping:
provider_mapping.update(mapping)
# Ensure the reverse mapping/index is updated (for faster lookups).
for name, index in six.iteritems(provider_mapping):
entries = self._reverse_mapping.setdefault(name, [])
provider = _Provider(provider_name, index)
if provider not in entries:
entries.append(provider)
@fasteners.read_locked
def fetch(self, name, many_handler=None):
"""Fetch a named ``execute`` result."""
def _many_handler(values):
# By default we just return the first of many (unless provided
# a different callback that can translate many results into
# something more meaningful).
return values[0]
if many_handler is None:
many_handler = _many_handler
try:
providers = self._reverse_mapping[name]
except KeyError:
exceptions.raise_with_cause(exceptions.NotFound,
"Name %r is not mapped as a produced"
" output by any providers" % name)
values = []
for provider in providers:
if provider.name is _TRANSIENT_PROVIDER:
values.append(_item_from_single(provider,
self._transients, name))
else:
try:
container = self._get(provider.name,
'last_results', 'failure',
_EXECUTE_STATES_WITH_RESULTS,
states.EXECUTE)
except exceptions.NotFound:
pass
else:
values.append(_item_from_single(provider,
container, name))
if not values:
raise exceptions.NotFound("Unable to find result %r,"
" searched %s" % (name, providers))
else:
return many_handler(values)
@fasteners.read_locked
def fetch_unsatisfied_args(self, atom_name, args_mapping,
scope_walker=None, optional_args=None):
"""Fetch unsatisfied ``execute`` arguments using an atoms args mapping.
NOTE(harlowja): this takes into account the provided scope walker
atoms who should produce the required value at runtime, as well as
the transient/persistent flow and atom specific injected arguments.
It does **not** check if the providers actually have produced the
needed values; it just checks that they are registered to produce
it in the future.
"""
def _fetch_providers(name):
"""Fetchs pair of (default providers, non-default providers)."""
default_providers = []
non_default_providers = []
for p in self._reverse_mapping.get(name, []):
if p.name in (_TRANSIENT_PROVIDER, self.injector_name):
default_providers.append(p)
else:
non_default_providers.append(p)
return default_providers, non_default_providers
def _locate_providers(name, scope_walker=None):
"""Finds the accessible *potential* providers."""
default_providers, non_default_providers = _fetch_providers(name)
providers = []
if non_default_providers:
if scope_walker is not None:
scope_iter = iter(scope_walker)
else:
scope_iter = iter([])
for names in scope_iter:
for p in non_default_providers:
if p.name in names:
providers.append(p)
for p in default_providers:
if p.name is _TRANSIENT_PROVIDER:
results = self._transients
else:
try:
results = self._get(p.name, 'last_results', 'failure',
_EXECUTE_STATES_WITH_RESULTS,
states.EXECUTE)
except exceptions.NotFound:
results = {}
try:
_item_from_single(p, results, name)
except exceptions.NotFound:
pass
else:
providers.append(p)
return providers
source, _clone = self._atomdetail_by_name(atom_name)
if scope_walker is None:
scope_walker = self._scope_fetcher(atom_name)
if optional_args is None:
optional_args = []
injected_sources = [
self._injected_args.get(atom_name, {}),
source.meta.get(META_INJECTED, {}),
]
missing = set(six.iterkeys(args_mapping))
for (bound_name, name) in six.iteritems(args_mapping):
if LOG.isEnabledFor(logging.BLATHER):
LOG.blather("Looking for %r <= %r for atom named: %s",
bound_name, name, atom_name)
if bound_name in optional_args:
LOG.blather("Argument %r is optional, skipping", bound_name)
missing.discard(bound_name)
continue
maybe_providers = 0
for source in injected_sources:
if not source:
continue
if name in source:
maybe_providers += 1
providers = _locate_providers(name, scope_walker=scope_walker)
maybe_providers += len(providers)
if maybe_providers:
LOG.blather("Atom %s will have %s potential providers"
" of %r <= %r", atom_name, maybe_providers,
bound_name, name)
missing.discard(bound_name)
return missing
@fasteners.read_locked
def fetch_all(self, many_handler=None):
"""Fetch all named ``execute`` results known so far."""
def _many_handler(values):
if len(values) > 1:
return values
return values[0]
if many_handler is None:
many_handler = _many_handler
results = {}
for name in six.iterkeys(self._reverse_mapping):
try:
results[name] = self.fetch(name, many_handler=many_handler)
except exceptions.NotFound:
pass
return results
@fasteners.read_locked
def fetch_mapped_args(self, args_mapping,
atom_name=None, scope_walker=None,
optional_args=None):
"""Fetch ``execute`` arguments for an atom using its args mapping."""
def _extract_first_from(name, sources):
"""Extracts/returns first occurence of key in list of dicts."""
for i, source in enumerate(sources):
if not source:
continue
if name in source:
return (i, source[name])
raise KeyError(name)
def _get_results(looking_for, provider):
"""Gets the results saved for a given provider."""
try:
return self._get(provider.name, 'last_results', 'failure',
_EXECUTE_STATES_WITH_RESULTS,
states.EXECUTE)
except exceptions.NotFound:
exceptions.raise_with_cause(exceptions.NotFound,
"Expected to be able to find"
" output %r produced by %s but was"
" unable to get at that providers"
" results" % (looking_for,
provider))
def _locate_providers(looking_for, possible_providers,
scope_walker=None):
"""Finds the accessible providers."""
default_providers = []
for p in possible_providers:
if p.name is _TRANSIENT_PROVIDER:
default_providers.append((p, self._transients))
if p.name == self.injector_name:
default_providers.append((p, _get_results(looking_for, p)))
if default_providers:
return default_providers
if scope_walker is not None:
scope_iter = iter(scope_walker)
else:
scope_iter = iter([])
extractor = lambda p: p.name
for names in scope_iter:
# *Always* retain the scope ordering (if any matches
# happen); instead of retaining the possible provider match
# order (which isn't that important and may be different from
# the scope requested ordering).
providers = misc.look_for(names, possible_providers,
extractor=extractor)
if providers:
return [(p, _get_results(looking_for, p))
for p in providers]
return []
if optional_args is None:
optional_args = []
if atom_name:
source, _clone = self._atomdetail_by_name(atom_name)
injected_sources = [
self._injected_args.get(atom_name, {}),
source.meta.get(META_INJECTED, {}),
]
if scope_walker is None:
scope_walker = self._scope_fetcher(atom_name)
else:
injected_sources = []
if not args_mapping:
return {}
mapped_args = {}
for (bound_name, name) in six.iteritems(args_mapping):
if LOG.isEnabledFor(logging.BLATHER):
if atom_name:
LOG.blather("Looking for %r <= %r for atom named: %s",
bound_name, name, atom_name)
else:
LOG.blather("Looking for %r <= %r", bound_name, name)
try:
source_index, value = _extract_first_from(name,
injected_sources)
mapped_args[bound_name] = value
if LOG.isEnabledFor(logging.BLATHER):
if source_index == 0:
LOG.blather("Matched %r <= %r to %r (from injected"
" atom-specific transient"
" values)", bound_name, name, value)
else:
LOG.blather("Matched %r <= %r to %r (from injected"
" atom-specific persistent"
" values)", bound_name, name, value)
except KeyError:
try:
possible_providers = self._reverse_mapping[name]
except KeyError:
if bound_name in optional_args:
LOG.blather("Argument %r is optional, skipping",
bound_name)
continue
raise exceptions.NotFound("Name %r is not mapped as a"
" produced output by any"
" providers" % name)
# Reduce the possible providers to one that are allowed.
providers = _locate_providers(name, possible_providers,
scope_walker=scope_walker)
if not providers:
raise exceptions.NotFound(
"Mapped argument %r <= %r was not produced"
" by any accessible provider (%s possible"
" providers were scanned)"
% (bound_name, name, len(possible_providers)))
provider, value = _item_from_first_of(providers, name)
mapped_args[bound_name] = value
LOG.blather("Matched %r <= %r to %r (from %s)",
bound_name, name, value, provider)
return mapped_args
@fasteners.write_locked
def set_flow_state(self, state):
"""Set flow details state and save it."""
source, clone = self._fetch_flowdetail(clone=True)
clone.state = state
self._with_connection(self._save_flow_detail, source, clone)
@fasteners.write_locked
def update_flow_metadata(self, update_with):
"""Update flowdetails metadata and save it."""
if update_with:
source, clone = self._fetch_flowdetail(clone=True)
clone.meta.update(update_with)
self._with_connection(self._save_flow_detail, source, clone)
@fasteners.read_locked
def get_flow_state(self):
"""Get state from flow details."""
source = self._flowdetail
state = source.state
if state is None:
state = states.PENDING
return state
def _translate_into_history(self, ad):
failure = None
if ad.failure is not None:
# NOTE(harlowja): Try to use our local cache to get a more
# complete failure object that has a traceback (instead of the
# one that is saved which will *typically* not have one)...
failure = ad.failure
fail_cache = self._failures[ad.name]
try:
fail = fail_cache[states.EXECUTE]
if failure.matches(fail):
failure = fail
except KeyError:
pass
return retry.History(ad.results, failure=failure)
@fasteners.read_locked
def get_retry_history(self, retry_name):
"""Fetch a single retrys history."""
source, _clone = self._atomdetail_by_name(
retry_name, expected_type=models.RetryDetail)
return self._translate_into_history(source)
@fasteners.read_locked
def get_retry_histories(self):
"""Fetch all retrys histories."""
histories = []
for ad in self._flowdetail:
if isinstance(ad, models.RetryDetail):
histories.append((ad.name,
self._translate_into_history(ad)))
return histories
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