openstack
/
taskflow
Code Issues Proposed changes

Rename logbook module -> models module 

Since this module contains more than the logbook
class and really is a our generic models that are used
to hold the runtime structure it is more appropriate to
place it under a models module and deprecate the usage
of the old module by placing a warning there (so that
when it is imported that warning is triggered).

Change-Id: I79def5ee08f560d38f2c9dcefd0b33becc2a4d36
This commit is contained in:
Joshua Harlow 2015-06-09 18:19:11 -07:00
parent df5fbe469c
commit 1e3dc09453
18 changed files with 1039 additions and 1002 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
doc/source/engines.rst
View File

@ -246,7 +246,7 @@ Preparation
This stage (see :py:func:`~taskflow.engines.base.Engine.prepare`) starts by
setting up the storage needed for all atoms in the compiled graph, ensuring
that corresponding :py:class:`~taskflow.persistence.logbook.AtomDetail` (or
that corresponding :py:class:`~taskflow.persistence.models.AtomDetail` (or
subclass of) objects are created for each node in the graph.
Validation
@ -293,7 +293,7 @@ for things like retry atom which can influence what a tasks intention should be
:py:class:`~taskflow.engines.action_engine.analyzer.Analyzer` helper
object which was designed to provide helper methods for this analysis). Once
these intentions are determined and associated with each task (the intention is
also stored in the :py:class:`~taskflow.persistence.logbook.AtomDetail` object)
also stored in the :py:class:`~taskflow.persistence.models.AtomDetail` object)
the :ref:`scheduling <scheduling>` stage starts.
.. _scheduling:
@ -323,8 +323,8 @@ submitted to complete. Once one of the future objects completes (or fails) that
atoms result will be examined and finalized using a
:py:class:`~taskflow.engines.action_engine.completer.Completer` implementation.
It typically will persist results to a provided persistence backend (saved
into the corresponding :py:class:`~taskflow.persistence.logbook.AtomDetail`
and :py:class:`~taskflow.persistence.logbook.FlowDetail` objects via the
into the corresponding :py:class:`~taskflow.persistence.models.AtomDetail`
and :py:class:`~taskflow.persistence.models.FlowDetail` objects via the
:py:class:`~taskflow.storage.Storage` helper) and reflect
the new state of the atom. At this point what typically happens falls into two
categories, one for if that atom failed and one for if it did not. If the atom

2
doc/source/jobs.rst
View File

@ -30,7 +30,7 @@ Definitions
Jobs
A :py:class:`job <taskflow.jobs.base.Job>` consists of a unique identifier,
name, and a reference to a :py:class:`logbook
<taskflow.persistence.logbook.LogBook>` which contains the details of the
<taskflow.persistence.models.LogBook>` which contains the details of the
work that has been or should be/will be completed to finish the work that has
been created for that job.

22
doc/source/persistence.rst
View File

@ -40,38 +40,38 @@ On :doc:`engine <engines>` construction typically a backend (it can be
optional) will be provided which satisfies the
:py:class:`~taskflow.persistence.base.Backend` abstraction. Along with
providing a backend object a
:py:class:`~taskflow.persistence.logbook.FlowDetail` object will also be
:py:class:`~taskflow.persistence.models.FlowDetail` object will also be
created and provided (this object will contain the details about the flow to be
ran) to the engine constructor (or associated :py:meth:`load()
<taskflow.engines.helpers.load>` helper functions). Typically a
:py:class:`~taskflow.persistence.logbook.FlowDetail` object is created from a
:py:class:`~taskflow.persistence.logbook.LogBook` object (the book object acts
as a type of container for :py:class:`~taskflow.persistence.logbook.FlowDetail`
and :py:class:`~taskflow.persistence.logbook.AtomDetail` objects).
:py:class:`~taskflow.persistence.models.FlowDetail` object is created from a
:py:class:`~taskflow.persistence.models.LogBook` object (the book object acts
as a type of container for :py:class:`~taskflow.persistence.models.FlowDetail`
and :py:class:`~taskflow.persistence.models.AtomDetail` objects).
**Preparation**: Once an engine starts to run it will create a
:py:class:`~taskflow.storage.Storage` object which will act as the engines
interface to the underlying backend storage objects (it provides helper
functions that are commonly used by the engine, avoiding repeating code when
interacting with the provided
:py:class:`~taskflow.persistence.logbook.FlowDetail` and
:py:class:`~taskflow.persistence.models.FlowDetail` and
:py:class:`~taskflow.persistence.base.Backend` objects). As an engine
initializes it will extract (or create)
:py:class:`~taskflow.persistence.logbook.AtomDetail` objects for each atom in
:py:class:`~taskflow.persistence.models.AtomDetail` objects for each atom in
the workflow the engine will be executing.
**Execution:** When an engine beings to execute (see :doc:`engine <engines>`
for more of the details about how an engine goes about this process) it will
examine any previously existing
:py:class:`~taskflow.persistence.logbook.AtomDetail` objects to see if they can
:py:class:`~taskflow.persistence.models.AtomDetail` objects to see if they can
be used for resuming; see :doc:`resumption <resumption>` for more details on
this subject. For atoms which have not finished (or did not finish correctly
from a previous run) they will begin executing only after any dependent inputs
are ready. This is done by analyzing the execution graph and looking at
predecessor :py:class:`~taskflow.persistence.logbook.AtomDetail` outputs and
predecessor :py:class:`~taskflow.persistence.models.AtomDetail` outputs and
states (which may have been persisted in a past run). This will result in
either using their previous information or by running those predecessors and
saving their output to the :py:class:`~taskflow.persistence.logbook.FlowDetail`
saving their output to the :py:class:`~taskflow.persistence.models.FlowDetail`
and :py:class:`~taskflow.persistence.base.Backend` objects. This
execution, analysis and interaction with the storage objects continues (what is
described here is a simplification of what really happens; which is quite a bit
@ -288,7 +288,7 @@ Interfaces
Models
======
.. automodule:: taskflow.persistence.logbook
.. automodule:: taskflow.persistence.models
Implementations
===============

14
doc/source/resumption.rst
View File

@ -46,7 +46,7 @@ name serves a special purpose in the resumption process (as well as serving a
useful purpose when running, allowing for atom identification in the
:doc:`notification <notifications>` process). The reason for having names is
that an atom in a flow needs to be somehow matched with (a potentially)
existing :py:class:`~taskflow.persistence.logbook.AtomDetail` during engine
existing :py:class:`~taskflow.persistence.models.AtomDetail` during engine
resumption & subsequent running.
The match should be:
@ -71,9 +71,9 @@ Scenarios
=========
When new flow is loaded into engine, there is no persisted data for it yet, so
a corresponding :py:class:`~taskflow.persistence.logbook.FlowDetail` object
a corresponding :py:class:`~taskflow.persistence.models.FlowDetail` object
will be created, as well as a
:py:class:`~taskflow.persistence.logbook.AtomDetail` object for each atom that
:py:class:`~taskflow.persistence.models.AtomDetail` object for each atom that
is contained in it. These will be immediately saved into the persistence
backend that is configured. If no persistence backend is configured, then as
expected nothing will be saved and the atoms and flow will be ran in a
@ -94,7 +94,7 @@ When the factory function mentioned above returns the exact same the flow and
atoms (no changes are performed).
**Runtime change:** Nothing should be done -- the engine will re-associate
atoms with :py:class:`~taskflow.persistence.logbook.AtomDetail` objects by name
atoms with :py:class:`~taskflow.persistence.models.AtomDetail` objects by name
and then the engine resumes.
Atom was added
@ -105,7 +105,7 @@ in (for example for changing the runtime structure of what was previously ran
in the first run).
**Runtime change:** By default when the engine resumes it will notice that a
corresponding :py:class:`~taskflow.persistence.logbook.AtomDetail` does not
corresponding :py:class:`~taskflow.persistence.models.AtomDetail` does not
exist and one will be created and associated.
Atom was removed
@ -134,7 +134,7 @@ factory should replace this name where it was being used previously.
exist when a new atom is added. In the future TaskFlow could make this easier
by providing a ``upgrade()`` function that can be used to give users the
ability to upgrade atoms before running (manual introspection & modification of
a :py:class:`~taskflow.persistence.logbook.LogBook` can be done before engine
a :py:class:`~taskflow.persistence.models.LogBook` can be done before engine
loading and running to accomplish this in the meantime).
Atom was split in two atoms or merged
@ -150,7 +150,7 @@ exist when a new atom is added or removed. In the future TaskFlow could make
this easier by providing a ``migrate()`` function that can be used to give
users the ability to migrate atoms previous data before running (manual
introspection & modification of a
:py:class:`~taskflow.persistence.logbook.LogBook` can be done before engine
:py:class:`~taskflow.persistence.models.LogBook` can be done before engine
loading and running to accomplish this in the meantime).
Flow structure was changed

4
taskflow/examples/persistence_example.py
View File

@ -31,7 +31,7 @@ sys.path.insert(0, self_dir)
from taskflow import engines
from taskflow.patterns import linear_flow as lf
from taskflow.persistence import logbook
from taskflow.persistence import models
from taskflow import task
from taskflow.utils import persistence_utils as p_utils
@ -94,7 +94,7 @@ with eu.get_backend(backend_uri) as backend:
# Make a flow that will blow up if the file didn't exist previously, if it
# did exist, assume we won't blow up (and therefore this shows the undo
# and redo that a flow will go through).
book = logbook.LogBook("my-test")
book = models.LogBook("my-test")
flow = make_flow(blowup=blowup)
eu.print_wrapped("Running")
try:

8
taskflow/examples/tox_conductor.py
View File

@ -42,7 +42,7 @@ from taskflow import engines
from taskflow.jobs import backends as boards
from taskflow.patterns import linear_flow
from taskflow.persistence import backends as persistence
from taskflow.persistence import logbook
from taskflow.persistence import models
from taskflow import task
from taskflow.utils import threading_utils
@ -145,9 +145,9 @@ def generate_reviewer(client, saver, name=NAME):
def make_save_book(saver, review_id):
# Record what we want to happen (sometime in the future).
book = logbook.LogBook("book_%s" % review_id)
detail = logbook.FlowDetail("flow_%s" % review_id,
uuidutils.generate_uuid())
book = models.LogBook("book_%s" % review_id)
detail = models.FlowDetail("flow_%s" % review_id,
uuidutils.generate_uuid())
book.add(detail)
# Associate the factory method we want to be called (in the future)
# with the book, so that the conductor will be able to call into

10
taskflow/persistence/backends/impl_sqlalchemy.py
View File

@ -34,7 +34,7 @@ from taskflow import logging
from taskflow.persistence.backends.sqlalchemy import migration
from taskflow.persistence.backends.sqlalchemy import tables
from taskflow.persistence import base
from taskflow.persistence import logbook
from taskflow.persistence import models
from taskflow.types import failure
from taskflow.utils import eventlet_utils
from taskflow.utils import misc
@ -194,16 +194,16 @@ class _Alchemist(object):
@staticmethod
def convert_flow_detail(row):
return logbook.FlowDetail.from_dict(dict(row.items()))
return models.FlowDetail.from_dict(dict(row.items()))
@staticmethod
def convert_book(row):
return logbook.LogBook.from_dict(dict(row.items()))
return models.LogBook.from_dict(dict(row.items()))
@staticmethod
def convert_atom_detail(row):
row = dict(row.items())
atom_cls = logbook.atom_detail_class(row.pop('atom_type'))
atom_cls = models.atom_detail_class(row.pop('atom_type'))
return atom_cls.from_dict(row)
def atom_query_iter(self, conn, parent_uuid):
@ -457,7 +457,7 @@ class Connection(base.Connection):
def _insert_atom_details(self, conn, ad, parent_uuid):
value = ad.to_dict()
value['parent_uuid'] = parent_uuid
value['atom_type'] = logbook.atom_detail_type(ad)
value['atom_type'] = models.atom_detail_type(ad)
conn.execute(sql.insert(self._tables.atomdetails, value))
def _update_atom_details(self, conn, ad, e_ad):

4
taskflow/persistence/backends/sqlalchemy/alembic/versions/84d6e888850_add_task_detail_type.py
View File

@ -29,11 +29,11 @@ down_revision = '1c783c0c2875'
from alembic import op
import sqlalchemy as sa
from taskflow.persistence import logbook
from taskflow.persistence import models
def upgrade():
atom_types = sa.Enum(*logbook.ATOM_TYPES, name='atom_types')
atom_types = sa.Enum(*models.ATOM_TYPES, name='atom_types')
column = sa.Column('atom_type', atom_types)
bind = op.get_bind()
impl = atom_types.dialect_impl(bind.dialect)

4
taskflow/persistence/backends/sqlalchemy/tables.py
View File

@ -22,7 +22,7 @@ from oslo_utils import uuidutils
from sqlalchemy import Table, Column, String, ForeignKey, DateTime, Enum
from sqlalchemy import types
from taskflow.persistence import logbook
from taskflow.persistence import models
from taskflow import states
Tables = collections.namedtuple('Tables',
@ -92,7 +92,7 @@ def fetch(metadata):
default=uuidutils.generate_uuid),
Column('failure', Json),
Column('results', Json),
Column('atom_type', Enum(*logbook.ATOM_TYPES,
Column('atom_type', Enum(*models.ATOM_TYPES,
name='atom_types')),
Column('intention', Enum(*states.INTENTIONS,
name='intentions')))

4
taskflow/persistence/base.py
View File

@ -18,7 +18,7 @@ import abc
import six
from taskflow.persistence import logbook
from taskflow.persistence import models
@six.add_metaclass(abc.ABCMeta)
@ -125,5 +125,5 @@ class Connection(object):
def _format_atom(atom_detail):
return {
'atom': atom_detail.to_dict(),
'type': logbook.atom_detail_type(atom_detail),
'type': models.atom_detail_type(atom_detail),
}

889
taskflow/persistence/logbook.py
View File

@ -1,7 +1,6 @@
# -*- coding: utf-8 -*-
# Copyright (C) 2012 Yahoo! Inc. All Rights Reserved.
# Copyright (C) 2013 Rackspace Hosting All Rights Reserved.
# Copyright (C) 2015 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
@ -15,878 +14,24 @@
# License for the specific language governing permissions and limitations
# under the License.
import abc
import copy
from debtcollector import removals
from oslo_utils import timeutils
from oslo_utils import uuidutils
import six
from taskflow.persistence import models
from taskflow import exceptions as exc
from taskflow import logging
from taskflow import states
from taskflow.types import failure as ft
LOG = logging.getLogger(__name__)
# TODO(harlowja): remove me in a future version, since the models
# module is more appropriately named to what the objects in it are used for...
removals.removed_module(__name__, replacement="'%s'" % models.__name__,
version="0.11", removal_version='?',
stacklevel=4)
# Internal helpers...
def _copy_function(deep_copy):
if deep_copy:
return copy.deepcopy
else:
return lambda x: x
def _safe_marshal_time(when):
if not when:
return None
return timeutils.marshall_now(now=when)
def _safe_unmarshal_time(when):
if not when:
return None
return timeutils.unmarshall_time(when)
def _fix_meta(data):
# Handle the case where older schemas allowed this to be non-dict by
# correcting this case by replacing it with a dictionary when a non-dict
# is found.
meta = data.get('meta')
if not isinstance(meta, dict):
meta = {}
return meta
class LogBook(object):
"""A collection of flow details and associated metadata.
Typically this class contains a collection of flow detail entries
for a given engine (or job) so that those entities can track what 'work'
has been completed for resumption, reverting and miscellaneous tracking
purposes.
The data contained within this class need **not** be persisted to the
backend storage in real time. The data in this class will only be
guaranteed to be persisted when a save occurs via some backend
connection.
NOTE(harlowja): the naming of this class is analogous to a ship's log or a
similar type of record used in detailing work that has been completed (or
work that has not been completed).
:ivar created_at: A ``datetime.datetime`` object of when this logbook
was created.
:ivar updated_at: A ``datetime.datetime`` object of when this logbook
was last updated at.
:ivar meta: A dictionary of meta-data associated with this logbook.
"""
def __init__(self, name, uuid=None):
if uuid:
self._uuid = uuid
else:
self._uuid = uuidutils.generate_uuid()
self._name = name
self._flowdetails_by_id = {}
self.created_at = timeutils.utcnow()
self.updated_at = None
self.meta = {}
def add(self, fd):
"""Adds a new flow detail into this logbook.
NOTE(harlowja): if an existing flow detail exists with the same
uuid the existing one will be overwritten with the newly provided
one.
Does not *guarantee* that the details will be immediately saved.
"""
self._flowdetails_by_id[fd.uuid] = fd
self.updated_at = timeutils.utcnow()
def find(self, flow_uuid):
"""Locate the flow detail corresponding to the given uuid.
:returns: the flow detail with that uuid
:rtype: :py:class:`.FlowDetail` (or ``None`` if not found)
"""
return self._flowdetails_by_id.get(flow_uuid, None)
def merge(self, lb, deep_copy=False):
"""Merges the current object state with the given ones state.
If ``deep_copy`` is provided as truthy then the
local object will use ``copy.deepcopy`` to replace this objects
local attributes with the provided objects attributes (**only** if
there is a difference between this objects attributes and the
provided attributes). If ``deep_copy`` is falsey (the default) then a
reference copy will occur instead when a difference is detected.
NOTE(harlowja): If the provided object is this object itself
then **no** merging is done. Also note that this does **not** merge
the flow details contained in either.
:returns: this logbook (freshly merged with the incoming object)
:rtype: :py:class:`.LogBook`
"""
if lb is self:
return self
copy_fn = _copy_function(deep_copy)
if self.meta != lb.meta:
self.meta = copy_fn(lb.meta)
if lb.created_at != self.created_at:
self.created_at = copy_fn(lb.created_at)
if lb.updated_at != self.updated_at:
self.updated_at = copy_fn(lb.updated_at)
return self
def to_dict(self, marshal_time=False):
"""Translates the internal state of this object to a ``dict``.
NOTE(harlowja): The returned ``dict`` does **not** include any
contained flow details.
:returns: this logbook in ``dict`` form
"""
if not marshal_time:
marshal_fn = lambda x: x
else:
marshal_fn = _safe_marshal_time
return {
'name': self.name,
'meta': self.meta,
'uuid': self.uuid,
'updated_at': marshal_fn(self.updated_at),
'created_at': marshal_fn(self.created_at),
}
@classmethod
def from_dict(cls, data, unmarshal_time=False):
"""Translates the given ``dict`` into an instance of this class.
NOTE(harlowja): the ``dict`` provided should come from a prior
call to :meth:`.to_dict`.
:returns: a new logbook
:rtype: :py:class:`.LogBook`
"""
if not unmarshal_time:
unmarshal_fn = lambda x: x
else:
unmarshal_fn = _safe_unmarshal_time
obj = cls(data['name'], uuid=data['uuid'])
obj.updated_at = unmarshal_fn(data['updated_at'])
obj.created_at = unmarshal_fn(data['created_at'])
obj.meta = _fix_meta(data)
return obj
@property
def uuid(self):
"""The unique identifer of this logbook."""
return self._uuid
@property
def name(self):
"""The name of this logbook."""
return self._name
def __iter__(self):
for fd in six.itervalues(self._flowdetails_by_id):
yield fd
def __len__(self):
return len(self._flowdetails_by_id)
def copy(self, retain_contents=True):
"""Copies this logbook.
Creates a shallow copy of this logbook. If this logbook contains
flow details and ``retain_contents`` is truthy (the default) then
the flow details container will be shallow copied (the flow details
contained there-in will **not** be copied). If ``retain_contents`` is
falsey then the copied logbook will have **no** contained flow
details (but it will have the rest of the local objects attributes
copied).
:returns: a new logbook
:rtype: :py:class:`.LogBook`
"""
clone = copy.copy(self)
if not retain_contents:
clone._flowdetails_by_id = {}
else:
clone._flowdetails_by_id = self._flowdetails_by_id.copy()
if self.meta:
clone.meta = self.meta.copy()
return clone
class FlowDetail(object):
"""A collection of atom details and associated metadata.
Typically this class contains a collection of atom detail entries that
represent the atoms in a given flow structure (along with any other needed
metadata relevant to that flow).
The data contained within this class need **not** be persisted to the
backend storage in real time. The data in this class will only be
guaranteed to be persisted when a save (or update) occurs via some backend
connection.
:ivar state: The state of the flow associated with this flow detail.
:ivar meta: A dictionary of meta-data associated with this flow detail.
"""
def __init__(self, name, uuid):
self._uuid = uuid
self._name = name
self._atomdetails_by_id = {}
self.state = None
self.meta = {}
def update(self, fd):
"""Updates the objects state to be the same as the given one.
This will assign the private and public attributes of the given
flow detail directly to this object (replacing any existing
attributes in this object; even if they are the **same**).
NOTE(harlowja): If the provided object is this object itself
then **no** update is done.
:returns: this flow detail
:rtype: :py:class:`.FlowDetail`
"""
if fd is self:
return self
self._atomdetails_by_id = fd._atomdetails_by_id
self.state = fd.state
self.meta = fd.meta
return self
def merge(self, fd, deep_copy=False):
"""Merges the current object state with the given one's state.
If ``deep_copy`` is provided as truthy then the
local object will use ``copy.deepcopy`` to replace this objects
local attributes with the provided objects attributes (**only** if
there is a difference between this objects attributes and the
provided attributes). If ``deep_copy`` is falsey (the default) then a
reference copy will occur instead when a difference is detected.
NOTE(harlowja): If the provided object is this object itself
then **no** merging is done. Also this does **not** merge the atom
details contained in either.
:returns: this flow detail (freshly merged with the incoming object)
:rtype: :py:class:`.FlowDetail`
"""
if fd is self:
return self
copy_fn = _copy_function(deep_copy)
if self.meta != fd.meta:
self.meta = copy_fn(fd.meta)
if self.state != fd.state:
# NOTE(imelnikov): states are just strings, no need to copy.
self.state = fd.state
return self
def copy(self, retain_contents=True):
"""Copies this flow detail.
Creates a shallow copy of this flow detail. If this detail contains
flow details and ``retain_contents`` is truthy (the default) then
the atom details container will be shallow copied (the atom details
contained there-in will **not** be copied). If ``retain_contents`` is
falsey then the copied flow detail will have **no** contained atom
details (but it will have the rest of the local objects attributes
copied).
:returns: a new flow detail
:rtype: :py:class:`.FlowDetail`
"""
clone = copy.copy(self)
if not retain_contents:
clone._atomdetails_by_id = {}
else:
clone._atomdetails_by_id = self._atomdetails_by_id.copy()
if self.meta:
clone.meta = self.meta.copy()
return clone
def to_dict(self):
"""Translates the internal state of this object to a ``dict``.
NOTE(harlowja): The returned ``dict`` does **not** include any
contained atom details.
:returns: this flow detail in ``dict`` form
"""
return {
'name': self.name,
'meta': self.meta,
'state': self.state,
'uuid': self.uuid,
}
@classmethod
def from_dict(cls, data):
"""Translates the given ``dict`` into an instance of this class.
NOTE(harlowja): the ``dict`` provided should come from a prior
call to :meth:`.to_dict`.
:returns: a new flow detail
:rtype: :py:class:`.FlowDetail`
"""
obj = cls(data['name'], data['uuid'])
obj.state = data.get('state')
obj.meta = _fix_meta(data)
return obj
def add(self, ad):
"""Adds a new atom detail into this flow detail.
NOTE(harlowja): if an existing atom detail exists with the same
uuid the existing one will be overwritten with the newly provided
one.
Does not *guarantee* that the details will be immediately saved.
"""
self._atomdetails_by_id[ad.uuid] = ad
def find(self, ad_uuid):
"""Locate the atom detail corresponding to the given uuid.
:returns: the atom detail with that uuid
:rtype: :py:class:`.AtomDetail` (or ``None`` if not found)
"""
return self._atomdetails_by_id.get(ad_uuid)
@property
def uuid(self):
"""The unique identifer of this flow detail."""
return self._uuid
@property
def name(self):
"""The name of this flow detail."""
return self._name
def __iter__(self):
for ad in six.itervalues(self._atomdetails_by_id):
yield ad
def __len__(self):
return len(self._atomdetails_by_id)
@six.add_metaclass(abc.ABCMeta)
class AtomDetail(object):
"""A collection of atom specific runtime information and metadata.
This is a base **abstract** class that contains attributes that are used
to connect a atom to the persistence layer before, during, or after it is
running. It includes any results it may have produced, any state that it
may be in (for example ``FAILURE``), any exception that occurred when
running, and any associated stacktrace that may have occurring during an
exception being thrown. It may also contain any other metadata that
should also be stored along-side the details about the connected atom.
The data contained within this class need **not** be persisted to the
backend storage in real time. The data in this class will only be
guaranteed to be persisted when a save (or update) occurs via some backend
connection.
:ivar state: The state of the atom associated with this atom detail.
:ivar intention: The execution strategy of the atom associated
with this atom detail (used by an engine/others to
determine if the associated atom needs to be
executed, reverted, retried and so-on).
:ivar meta: A dictionary of meta-data associated with this atom detail.
:ivar version: A version tuple or string that represents the
atom version this atom detail is associated with (typically
used for introspection and any data migration
strategies).
:ivar results: Any results the atom produced from either its
``execute`` method or from other sources.
:ivar failure: If the atom failed (possibly due to its ``execute``
method raising) this will be a
:py:class:`~taskflow.types.failure.Failure` object that
represents that failure (if there was no failure this
will be set to none).
"""
def __init__(self, name, uuid):
self._uuid = uuid
self._name = name
self.state = None
self.intention = states.EXECUTE
self.results = None
self.failure = None
self.meta = {}
self.version = None
@staticmethod
def _was_failure(state, result):
# Internal helper method...
return state == states.FAILURE and isinstance(result, ft.Failure)
@property
def last_results(self):
"""Gets the atoms last result.
If the atom has produced many results (for example if it has been
retried, reverted, executed and ...) this returns the last one of
many results.
"""
return self.results
def update(self, ad):
"""Updates the object's state to be the same as the given one.
This will assign the private and public attributes of the given
atom detail directly to this object (replacing any existing
attributes in this object; even if they are the **same**).
NOTE(harlowja): If the provided object is this object itself
then **no** update is done.
:returns: this atom detail
:rtype: :py:class:`.AtomDetail`
"""
if ad is self:
return self
self.state = ad.state
self.intention = ad.intention
self.meta = ad.meta
self.failure = ad.failure
self.results = ad.results
self.version = ad.version
return self
@abc.abstractmethod
def merge(self, other, deep_copy=False):
"""Merges the current object state with the given ones state.
If ``deep_copy`` is provided as truthy then the
local object will use ``copy.deepcopy`` to replace this objects
local attributes with the provided objects attributes (**only** if
there is a difference between this objects attributes and the
provided attributes). If ``deep_copy`` is falsey (the default) then a
reference copy will occur instead when a difference is detected.
NOTE(harlowja): If the provided object is this object itself
then **no** merging is done. Do note that **no** results are merged
in this method. That operation **must** to be the responsibilty of
subclasses to implement and override this abstract method
and provide that merging themselves as they see fit.
:returns: this atom detail (freshly merged with the incoming object)
:rtype: :py:class:`.AtomDetail`
"""
copy_fn = _copy_function(deep_copy)
# NOTE(imelnikov): states and intentions are just strings,
# so there is no need to copy them (strings are immutable in python).
self.state = other.state
self.intention = other.intention
if self.failure != other.failure:
# NOTE(imelnikov): we can't just deep copy Failures, as they
# contain tracebacks, which are not copyable.
if other.failure:
if deep_copy:
self.failure = other.failure.copy()
else:
self.failure = other.failure
else:
self.failure = None
if self.meta != other.meta:
self.meta = copy_fn(other.meta)
if self.version != other.version:
self.version = copy_fn(other.version)
return self
@abc.abstractmethod
def put(self, state, result):
"""Puts a result (acquired in the given state) into this detail."""
def to_dict(self):
"""Translates the internal state of this object to a ``dict``.
:returns: this atom detail in ``dict`` form
"""
if self.failure:
failure = self.failure.to_dict()
else:
failure = None
return {
'failure': failure,
'meta': self.meta,
'name': self.name,
'results': self.results,
'state': self.state,
'version': self.version,
'intention': self.intention,
'uuid': self.uuid,
}
@classmethod
def from_dict(cls, data):
"""Translates the given ``dict`` into an instance of this class.
NOTE(harlowja): the ``dict`` provided should come from a prior
call to :meth:`.to_dict`.
:returns: a new atom detail
:rtype: :py:class:`.AtomDetail`
"""
obj = cls(data['name'], data['uuid'])
obj.state = data.get('state')
obj.intention = data.get('intention')
obj.results = data.get('results')
obj.version = data.get('version')
obj.meta = _fix_meta(data)
failure = data.get('failure')
if failure:
obj.failure = ft.Failure.from_dict(failure)
return obj
@property
def uuid(self):
"""The unique identifer of this atom detail."""
return self._uuid
@property
def name(self):
"""The name of this atom detail."""
return self._name
@abc.abstractmethod
def reset(self, state):
"""Resets this atom detail and sets ``state`` attribute value."""
@abc.abstractmethod
def copy(self):
"""Copies this atom detail."""
class TaskDetail(AtomDetail):
"""A task detail (an atom detail typically associated with a |tt| atom).
.. |tt| replace:: :py:class:`~taskflow.task.BaseTask`
"""
def reset(self, state):
"""Resets this task detail and sets ``state`` attribute value.
This sets any previously set ``results`` and ``failure`` attributes
back to ``None`` and sets the state to the provided one, as well as
setting this task details ``intention`` attribute to ``EXECUTE``.
"""
self.results = None
self.failure = None
self.state = state
self.intention = states.EXECUTE
def put(self, state, result):
"""Puts a result (acquired in the given state) into this detail.
If the result is a :py:class:`~taskflow.types.failure.Failure` object
then the ``failure`` attribute will be set (and the ``results``
attribute will be set to ``None``); if the result is not a
:py:class:`~taskflow.types.failure.Failure` object then the
``results`` attribute will be set (and the ``failure`` attribute
will be set to ``None``). In either case the ``state``
attribute will be set to the provided state.
"""
was_altered = False
if self.state != state:
self.state = state
was_altered = True
if self._was_failure(state, result):
if self.failure != result:
self.failure = result
was_altered = True
if self.results is not None:
self.results = None
was_altered = True
else:
# We don't really have the ability to determine equality of
# task (user) results at the current time, without making
# potentially bad guesses, so assume the task detail always needs
# to be saved if they are not exactly equivalent...
if self.results is not result:
self.results = result
was_altered = True
if self.failure is not None:
self.failure = None
was_altered = True
return was_altered
def merge(self, other, deep_copy=False):
"""Merges the current task detail with the given one.
NOTE(harlowja): This merge does **not** copy and replace
the ``results`` attribute if it differs. Instead the current
objects ``results`` attribute directly becomes (via assignment) the
other objects ``results`` attribute. Also note that if the provided
object is this object itself then **no** merging is done.
See: https://bugs.launchpad.net/taskflow/+bug/1452978 for
what happens if this is copied at a deeper level (for example by
using ``copy.deepcopy`` or by using ``copy.copy``).
:returns: this task detail (freshly merged with the incoming object)
:rtype: :py:class:`.TaskDetail`
"""
if not isinstance(other, TaskDetail):
raise exc.NotImplementedError("Can only merge with other"
" task details")
if other is self:
return self
super(TaskDetail, self).merge(other, deep_copy=deep_copy)
if self.results != other.results:
self.results = other.results
return self
def copy(self):
"""Copies this task detail.
Creates a shallow copy of this task detail (any meta-data and
version information that this object maintains is shallow
copied via ``copy.copy``).
NOTE(harlowja): This copy does **not** perform ``copy.copy`` on
the ``results`` attribute of this object (before assigning to the
copy). Instead the current objects ``results`` attribute directly
becomes (via assignment) the copied objects ``results`` attribute.
See: https://bugs.launchpad.net/taskflow/+bug/1452978 for
what happens if this is copied at a deeper level (for example by
using ``copy.deepcopy`` or by using ``copy.copy``).
:returns: a new task detail
:rtype: :py:class:`.TaskDetail`
"""
clone = copy.copy(self)
clone.results = self.results
if self.meta:
clone.meta = self.meta.copy()
if self.version:
clone.version = copy.copy(self.version)
return clone
class RetryDetail(AtomDetail):
"""A retry detail (an atom detail typically associated with a |rt| atom).
.. |rt| replace:: :py:class:`~taskflow.retry.Retry`
"""
def __init__(self, name, uuid):
super(RetryDetail, self).__init__(name, uuid)
self.results = []
def reset(self, state):
"""Resets this retry detail and sets ``state`` attribute value.
This sets any previously added ``results`` back to an empty list
and resets the ``failure`` attribute back to ``None`` and sets the
state to the provided one, as well as setting this atom
details ``intention`` attribute to ``EXECUTE``.
"""
self.results = []
self.failure = None
self.state = state
self.intention = states.EXECUTE
def copy(self):
"""Copies this retry detail.
Creates a shallow copy of this retry detail (any meta-data and
version information that this object maintains is shallow
copied via ``copy.copy``).
NOTE(harlowja): This copy does **not** copy
the incoming objects ``results`` attribute. Instead this
objects ``results`` attribute list is iterated over and a new list
is constructed with each ``(data, failures)`` element in that list
having its ``failures`` (a dictionary of each named
:py:class:`~taskflow.types.failure.Failure` object that
occured) copied but its ``data`` is left untouched. After
this is done that new list becomes (via assignment) the cloned
objects ``results`` attribute.
See: https://bugs.launchpad.net/taskflow/+bug/1452978 for
what happens if the ``data`` in ``results`` is copied at a
deeper level (for example by using ``copy.deepcopy`` or by
using ``copy.copy``).
:returns: a new retry detail
:rtype: :py:class:`.RetryDetail`
"""
clone = copy.copy(self)
results = []
# NOTE(imelnikov): we can't just deep copy Failures, as they
# contain tracebacks, which are not copyable.
for (data, failures) in self.results:
copied_failures = {}
for (key, failure) in six.iteritems(failures):
copied_failures[key] = failure
results.append((data, copied_failures))
clone.results = results
if self.meta:
clone.meta = self.meta.copy()
if self.version:
clone.version = copy.copy(self.version)
return clone
@property
def last_results(self):
"""The last result that was produced."""
try:
return self.results[-1][0]
except IndexError:
exc.raise_with_cause(exc.NotFound, "Last results not found")
@property
def last_failures(self):
"""The last failure dictionary that was produced.
NOTE(harlowja): This is **not** the same as the
local ``failure`` attribute as the obtained failure dictionary in
the ``results`` attribute (which is what this returns) is from
associated atom failures (which is different from the directly
related failure of the retry unit associated with this
atom detail).
"""
try:
return self.results[-1][1]
except IndexError:
exc.raise_with_cause(exc.NotFound, "Last failures not found")
def put(self, state, result):
"""Puts a result (acquired in the given state) into this detail.
If the result is a :py:class:`~taskflow.types.failure.Failure` object
then the ``failure`` attribute will be set; if the result is not a
:py:class:`~taskflow.types.failure.Failure` object then the
``results`` attribute will be appended to (and the ``failure``
attribute will be set to ``None``). In either case the ``state``
attribute will be set to the provided state.
"""
# Do not clean retry history (only on reset does this happen).
self.state = state
if self._was_failure(state, result):
self.failure = result
else:
self.results.append((result, {}))
self.failure = None
return True
@classmethod
def from_dict(cls, data):
"""Translates the given ``dict`` into an instance of this class."""
def decode_results(results):
if not results:
return []
new_results = []
for (data, failures) in results:
new_failures = {}
for (key, data) in six.iteritems(failures):
new_failures[key] = ft.Failure.from_dict(data)
new_results.append((data, new_failures))
return new_results
obj = super(RetryDetail, cls).from_dict(data)
obj.results = decode_results(obj.results)
return obj
def to_dict(self):
"""Translates the internal state of this object to a ``dict``."""
def encode_results(results):
if not results:
return []
new_results = []
for (data, failures) in results:
new_failures = {}
for (key, failure) in six.iteritems(failures):
new_failures[key] = failure.to_dict()
new_results.append((data, new_failures))
return new_results
base = super(RetryDetail, self).to_dict()
base['results'] = encode_results(base.get('results'))
return base
def merge(self, other, deep_copy=False):
"""Merges the current retry detail with the given one.
NOTE(harlowja): This merge does **not** deep copy
the incoming objects ``results`` attribute (if it differs). Instead
the incoming objects ``results`` attribute list is **always** iterated
over and a new list is constructed with
each ``(data, failures)`` element in that list having
its ``failures`` (a dictionary of each named
:py:class:`~taskflow.types.failure.Failure` objects that
occurred) copied but its ``data`` is left untouched. After
this is done that new list becomes (via assignment) this
objects ``results`` attribute. Also note that if the provided object
is this object itself then **no** merging is done.
See: https://bugs.launchpad.net/taskflow/+bug/1452978 for
what happens if the ``data`` in ``results`` is copied at a
deeper level (for example by using ``copy.deepcopy`` or by
using ``copy.copy``).
:returns: this retry detail (freshly merged with the incoming object)
:rtype: :py:class:`.RetryDetail`
"""
if not isinstance(other, RetryDetail):
raise exc.NotImplementedError("Can only merge with other"
" retry details")
if other is self:
return self
super(RetryDetail, self).merge(other, deep_copy=deep_copy)
results = []
# NOTE(imelnikov): we can't just deep copy Failures, as they
# contain tracebacks, which are not copyable.
for (data, failures) in other.results:
copied_failures = {}
for (key, failure) in six.iteritems(failures):
if deep_copy:
copied_failures[key] = failure.copy()
else:
copied_failures[key] = failure
results.append((data, copied_failures))
self.results = results
return self
_DETAIL_TO_NAME = {
RetryDetail: 'RETRY_DETAIL',
TaskDetail: 'TASK_DETAIL',
}
_NAME_TO_DETAIL = dict((name, cls)
for (cls, name) in six.iteritems(_DETAIL_TO_NAME))
ATOM_TYPES = list(six.iterkeys(_NAME_TO_DETAIL))
def atom_detail_class(atom_type):
try:
return _NAME_TO_DETAIL[atom_type]
except KeyError:
raise TypeError("Unknown atom type '%s'" % (atom_type))
def atom_detail_type(atom_detail):
try:
return _DETAIL_TO_NAME[type(atom_detail)]
except KeyError:
raise TypeError("Unknown atom '%s' (%s)"
% (atom_detail, type(atom_detail)))
# Keep alias classes/functions... around until this module is removed.
LogBook = models.LogBook
FlowDetail = models.FlowDetail
AtomDetail = models.AtomDetail
TaskDetail = models.TaskDetail
RetryDetail = models.RetryDetail
atom_detail_type = models.atom_detail_type
atom_detail_class = models.atom_detail_class
ATOM_TYPES = models.ATOM_TYPES

892
taskflow/persistence/models.py Normal file
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@ -0,0 +1,892 @@
# -*- coding: utf-8 -*-
# Copyright (C) 2012 Yahoo! Inc. All Rights Reserved.
# Copyright (C) 2013 Rackspace Hosting 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
from oslo_utils import timeutils
from oslo_utils import uuidutils
import six
from taskflow import exceptions as exc
from taskflow import logging
from taskflow import states
from taskflow.types import failure as ft
LOG = logging.getLogger(__name__)
# Internal helpers...
def _copy_function(deep_copy):
if deep_copy:
return copy.deepcopy
else:
return lambda x: x
def _safe_marshal_time(when):
if not when:
return None
return timeutils.marshall_now(now=when)
def _safe_unmarshal_time(when):
if not when:
return None
return timeutils.unmarshall_time(when)
def _fix_meta(data):
# Handle the case where older schemas allowed this to be non-dict by
# correcting this case by replacing it with a dictionary when a non-dict
# is found.
meta = data.get('meta')
if not isinstance(meta, dict):
meta = {}
return meta
class LogBook(object):
"""A collection of flow details and associated metadata.
Typically this class contains a collection of flow detail entries
for a given engine (or job) so that those entities can track what 'work'
has been completed for resumption, reverting and miscellaneous tracking
purposes.
The data contained within this class need **not** be persisted to the
backend storage in real time. The data in this class will only be
guaranteed to be persisted when a save occurs via some backend
connection.
NOTE(harlowja): the naming of this class is analogous to a ship's log or a
similar type of record used in detailing work that has been completed (or
work that has not been completed).
:ivar created_at: A ``datetime.datetime`` object of when this logbook
was created.
:ivar updated_at: A ``datetime.datetime`` object of when this logbook
was last updated at.
:ivar meta: A dictionary of meta-data associated with this logbook.
"""
def __init__(self, name, uuid=None):
if uuid:
self._uuid = uuid
else:
self._uuid = uuidutils.generate_uuid()
self._name = name
self._flowdetails_by_id = {}
self.created_at = timeutils.utcnow()
self.updated_at = None
self.meta = {}
def add(self, fd):
"""Adds a new flow detail into this logbook.
NOTE(harlowja): if an existing flow detail exists with the same
uuid the existing one will be overwritten with the newly provided
one.
Does not *guarantee* that the details will be immediately saved.
"""
self._flowdetails_by_id[fd.uuid] = fd
self.updated_at = timeutils.utcnow()
def find(self, flow_uuid):
"""Locate the flow detail corresponding to the given uuid.
:returns: the flow detail with that uuid
:rtype: :py:class:`.FlowDetail` (or ``None`` if not found)
"""
return self._flowdetails_by_id.get(flow_uuid, None)
def merge(self, lb, deep_copy=False):
"""Merges the current object state with the given ones state.
If ``deep_copy`` is provided as truthy then the
local object will use ``copy.deepcopy`` to replace this objects
local attributes with the provided objects attributes (**only** if
there is a difference between this objects attributes and the
provided attributes). If ``deep_copy`` is falsey (the default) then a
reference copy will occur instead when a difference is detected.
NOTE(harlowja): If the provided object is this object itself
then **no** merging is done. Also note that this does **not** merge
the flow details contained in either.
:returns: this logbook (freshly merged with the incoming object)
:rtype: :py:class:`.LogBook`
"""
if lb is self:
return self
copy_fn = _copy_function(deep_copy)
if self.meta != lb.meta:
self.meta = copy_fn(lb.meta)
if lb.created_at != self.created_at:
self.created_at = copy_fn(lb.created_at)
if lb.updated_at != self.updated_at:
self.updated_at = copy_fn(lb.updated_at)
return self
def to_dict(self, marshal_time=False):
"""Translates the internal state of this object to a ``dict``.
NOTE(harlowja): The returned ``dict`` does **not** include any
contained flow details.
:returns: this logbook in ``dict`` form
"""
if not marshal_time:
marshal_fn = lambda x: x
else:
marshal_fn = _safe_marshal_time
return {
'name': self.name,
'meta': self.meta,
'uuid': self.uuid,
'updated_at': marshal_fn(self.updated_at),
'created_at': marshal_fn(self.created_at),
}
@classmethod
def from_dict(cls, data, unmarshal_time=False):
"""Translates the given ``dict`` into an instance of this class.
NOTE(harlowja): the ``dict`` provided should come from a prior
call to :meth:`.to_dict`.
:returns: a new logbook
:rtype: :py:class:`.LogBook`
"""
if not unmarshal_time:
unmarshal_fn = lambda x: x
else:
unmarshal_fn = _safe_unmarshal_time
obj = cls(data['name'], uuid=data['uuid'])
obj.updated_at = unmarshal_fn(data['updated_at'])
obj.created_at = unmarshal_fn(data['created_at'])
obj.meta = _fix_meta(data)
return obj
@property
def uuid(self):
"""The unique identifer of this logbook."""
return self._uuid
@property
def name(self):
"""The name of this logbook."""
return self._name
def __iter__(self):
for fd in six.itervalues(self._flowdetails_by_id):
yield fd
def __len__(self):
return len(self._flowdetails_by_id)
def copy(self, retain_contents=True):
"""Copies this logbook.
Creates a shallow copy of this logbook. If this logbook contains
flow details and ``retain_contents`` is truthy (the default) then
the flow details container will be shallow copied (the flow details
contained there-in will **not** be copied). If ``retain_contents`` is
falsey then the copied logbook will have **no** contained flow
details (but it will have the rest of the local objects attributes
copied).
:returns: a new logbook
:rtype: :py:class:`.LogBook`
"""
clone = copy.copy(self)
if not retain_contents:
clone._flowdetails_by_id = {}
else:
clone._flowdetails_by_id = self._flowdetails_by_id.copy()
if self.meta:
clone.meta = self.meta.copy()
return clone
class FlowDetail(object):
"""A collection of atom details and associated metadata.
Typically this class contains a collection of atom detail entries that
represent the atoms in a given flow structure (along with any other needed
metadata relevant to that flow).
The data contained within this class need **not** be persisted to the
backend storage in real time. The data in this class will only be
guaranteed to be persisted when a save (or update) occurs via some backend
connection.
:ivar state: The state of the flow associated with this flow detail.
:ivar meta: A dictionary of meta-data associated with this flow detail.
"""
def __init__(self, name, uuid):
self._uuid = uuid
self._name = name
self._atomdetails_by_id = {}
self.state = None
self.meta = {}
def update(self, fd):
"""Updates the objects state to be the same as the given one.
This will assign the private and public attributes of the given
flow detail directly to this object (replacing any existing
attributes in this object; even if they are the **same**).
NOTE(harlowja): If the provided object is this object itself
then **no** update is done.
:returns: this flow detail
:rtype: :py:class:`.FlowDetail`
"""
if fd is self:
return self
self._atomdetails_by_id = fd._atomdetails_by_id
self.state = fd.state
self.meta = fd.meta
return self
def merge(self, fd, deep_copy=False):
"""Merges the current object state with the given one's state.
If ``deep_copy`` is provided as truthy then the
local object will use ``copy.deepcopy`` to replace this objects
local attributes with the provided objects attributes (**only** if
there is a difference between this objects attributes and the
provided attributes). If ``deep_copy`` is falsey (the default) then a
reference copy will occur instead when a difference is detected.
NOTE(harlowja): If the provided object is this object itself
then **no** merging is done. Also this does **not** merge the atom
details contained in either.
:returns: this flow detail (freshly merged with the incoming object)
:rtype: :py:class:`.FlowDetail`
"""
if fd is self:
return self
copy_fn = _copy_function(deep_copy)
if self.meta != fd.meta:
self.meta = copy_fn(fd.meta)
if self.state != fd.state:
# NOTE(imelnikov): states are just strings, no need to copy.
self.state = fd.state
return self
def copy(self, retain_contents=True):
"""Copies this flow detail.
Creates a shallow copy of this flow detail. If this detail contains
flow details and ``retain_contents`` is truthy (the default) then
the atom details container will be shallow copied (the atom details
contained there-in will **not** be copied). If ``retain_contents`` is
falsey then the copied flow detail will have **no** contained atom
details (but it will have the rest of the local objects attributes
copied).
:returns: a new flow detail
:rtype: :py:class:`.FlowDetail`
"""
clone = copy.copy(self)
if not retain_contents:
clone._atomdetails_by_id = {}
else:
clone._atomdetails_by_id = self._atomdetails_by_id.copy()
if self.meta:
clone.meta = self.meta.copy()
return clone
def to_dict(self):
"""Translates the internal state of this object to a ``dict``.
NOTE(harlowja): The returned ``dict`` does **not** include any
contained atom details.
:returns: this flow detail in ``dict`` form
"""
return {
'name': self.name,
'meta': self.meta,
'state': self.state,
'uuid': self.uuid,
}
@classmethod
def from_dict(cls, data):
"""Translates the given ``dict`` into an instance of this class.
NOTE(harlowja): the ``dict`` provided should come from a prior
call to :meth:`.to_dict`.
:returns: a new flow detail
:rtype: :py:class:`.FlowDetail`
"""
obj = cls(data['name'], data['uuid'])
obj.state = data.get('state')
obj.meta = _fix_meta(data)
return obj
def add(self, ad):
"""Adds a new atom detail into this flow detail.
NOTE(harlowja): if an existing atom detail exists with the same
uuid the existing one will be overwritten with the newly provided
one.
Does not *guarantee* that the details will be immediately saved.
"""
self._atomdetails_by_id[ad.uuid] = ad
def find(self, ad_uuid):
"""Locate the atom detail corresponding to the given uuid.
:returns: the atom detail with that uuid
:rtype: :py:class:`.AtomDetail` (or ``None`` if not found)
"""
return self._atomdetails_by_id.get(ad_uuid)
@property
def uuid(self):
"""The unique identifer of this flow detail."""
return self._uuid
@property
def name(self):
"""The name of this flow detail."""
return self._name
def __iter__(self):
for ad in six.itervalues(self._atomdetails_by_id):
yield ad
def __len__(self):
return len(self._atomdetails_by_id)
@six.add_metaclass(abc.ABCMeta)
class AtomDetail(object):
"""A collection of atom specific runtime information and metadata.
This is a base **abstract** class that contains attributes that are used
to connect a atom to the persistence layer before, during, or after it is
running. It includes any results it may have produced, any state that it
may be in (for example ``FAILURE``), any exception that occurred when
running, and any associated stacktrace that may have occurring during an
exception being thrown. It may also contain any other metadata that
should also be stored along-side the details about the connected atom.
The data contained within this class need **not** be persisted to the
backend storage in real time. The data in this class will only be
guaranteed to be persisted when a save (or update) occurs via some backend
connection.
:ivar state: The state of the atom associated with this atom detail.
:ivar intention: The execution strategy of the atom associated
with this atom detail (used by an engine/others to
determine if the associated atom needs to be
executed, reverted, retried and so-on).
:ivar meta: A dictionary of meta-data associated with this atom detail.
:ivar version: A version tuple or string that represents the
atom version this atom detail is associated with (typically
used for introspection and any data migration
strategies).
:ivar results: Any results the atom produced from either its
``execute`` method or from other sources.
:ivar failure: If the atom failed (possibly due to its ``execute``
method raising) this will be a
:py:class:`~taskflow.types.failure.Failure` object that
represents that failure (if there was no failure this
will be set to none).
"""
def __init__(self, name, uuid):
self._uuid = uuid
self._name = name
self.state = None
self.intention = states.EXECUTE
self.results = None
self.failure = None
self.meta = {}
self.version = None
@staticmethod
def _was_failure(state, result):
# Internal helper method...
return state == states.FAILURE and isinstance(result, ft.Failure)
@property
def last_results(self):
"""Gets the atoms last result.
If the atom has produced many results (for example if it has been
retried, reverted, executed and ...) this returns the last one of
many results.
"""
return self.results
def update(self, ad):
"""Updates the object's state to be the same as the given one.
This will assign the private and public attributes of the given
atom detail directly to this object (replacing any existing
attributes in this object; even if they are the **same**).
NOTE(harlowja): If the provided object is this object itself
then **no** update is done.
:returns: this atom detail
:rtype: :py:class:`.AtomDetail`
"""
if ad is self:
return self
self.state = ad.state
self.intention = ad.intention
self.meta = ad.meta
self.failure = ad.failure
self.results = ad.results
self.version = ad.version
return self
@abc.abstractmethod
def merge(self, other, deep_copy=False):
"""Merges the current object state with the given ones state.
If ``deep_copy`` is provided as truthy then the
local object will use ``copy.deepcopy`` to replace this objects
local attributes with the provided objects attributes (**only** if
there is a difference between this objects attributes and the
provided attributes). If ``deep_copy`` is falsey (the default) then a
reference copy will occur instead when a difference is detected.
NOTE(harlowja): If the provided object is this object itself
then **no** merging is done. Do note that **no** results are merged
in this method. That operation **must** to be the responsibilty of
subclasses to implement and override this abstract method
and provide that merging themselves as they see fit.
:returns: this atom detail (freshly merged with the incoming object)
:rtype: :py:class:`.AtomDetail`
"""
copy_fn = _copy_function(deep_copy)
# NOTE(imelnikov): states and intentions are just strings,
# so there is no need to copy them (strings are immutable in python).
self.state = other.state
self.intention = other.intention
if self.failure != other.failure:
# NOTE(imelnikov): we can't just deep copy Failures, as they
# contain tracebacks, which are not copyable.
if other.failure:
if deep_copy:
self.failure = other.failure.copy()
else:
self.failure = other.failure
else:
self.failure = None
if self.meta != other.meta:
self.meta = copy_fn(other.meta)
if self.version != other.version:
self.version = copy_fn(other.version)
return self
@abc.abstractmethod
def put(self, state, result):
"""Puts a result (acquired in the given state) into this detail."""
def to_dict(self):
"""Translates the internal state of this object to a ``dict``.
:returns: this atom detail in ``dict`` form
"""
if self.failure:
failure = self.failure.to_dict()
else:
failure = None
return {
'failure': failure,
'meta': self.meta,
'name': self.name,
'results': self.results,
'state': self.state,
'version': self.version,
'intention': self.intention,
'uuid': self.uuid,
}
@classmethod
def from_dict(cls, data):
"""Translates the given ``dict`` into an instance of this class.
NOTE(harlowja): the ``dict`` provided should come from a prior
call to :meth:`.to_dict`.
:returns: a new atom detail
:rtype: :py:class:`.AtomDetail`
"""
obj = cls(data['name'], data['uuid'])
obj.state = data.get('state')
obj.intention = data.get('intention')
obj.results = data.get('results')
obj.version = data.get('version')
obj.meta = _fix_meta(data)
failure = data.get('failure')
if failure:
obj.failure = ft.Failure.from_dict(failure)
return obj
@property
def uuid(self):
"""The unique identifer of this atom detail."""
return self._uuid
@property
def name(self):
"""The name of this atom detail."""
return self._name
@abc.abstractmethod
def reset(self, state):
"""Resets this atom detail and sets ``state`` attribute value."""
@abc.abstractmethod
def copy(self):
"""Copies this atom detail."""
class TaskDetail(AtomDetail):
"""A task detail (an atom detail typically associated with a |tt| atom).
.. |tt| replace:: :py:class:`~taskflow.task.BaseTask`
"""
def reset(self, state):
"""Resets this task detail and sets ``state`` attribute value.
This sets any previously set ``results`` and ``failure`` attributes
back to ``None`` and sets the state to the provided one, as well as
setting this task details ``intention`` attribute to ``EXECUTE``.
"""
self.results = None
self.failure = None
self.state = state
self.intention = states.EXECUTE
def put(self, state, result):
"""Puts a result (acquired in the given state) into this detail.
If the result is a :py:class:`~taskflow.types.failure.Failure` object
then the ``failure`` attribute will be set (and the ``results``
attribute will be set to ``None``); if the result is not a
:py:class:`~taskflow.types.failure.Failure` object then the
``results`` attribute will be set (and the ``failure`` attribute
will be set to ``None``). In either case the ``state``
attribute will be set to the provided state.
"""
was_altered = False
if self.state != state:
self.state = state
was_altered = True
if self._was_failure(state, result):
if self.failure != result:
self.failure = result
was_altered = True
if self.results is not None:
self.results = None
was_altered = True
else:
# We don't really have the ability to determine equality of
# task (user) results at the current time, without making
# potentially bad guesses, so assume the task detail always needs
# to be saved if they are not exactly equivalent...
if self.results is not result:
self.results = result
was_altered = True
if self.failure is not None:
self.failure = None
was_altered = True
return was_altered
def merge(self, other, deep_copy=False):
"""Merges the current task detail with the given one.
NOTE(harlowja): This merge does **not** copy and replace
the ``results`` attribute if it differs. Instead the current
objects ``results`` attribute directly becomes (via assignment) the
other objects ``results`` attribute. Also note that if the provided
object is this object itself then **no** merging is done.
See: https://bugs.launchpad.net/taskflow/+bug/1452978 for
what happens if this is copied at a deeper level (for example by
using ``copy.deepcopy`` or by using ``copy.copy``).
:returns: this task detail (freshly merged with the incoming object)
:rtype: :py:class:`.TaskDetail`
"""
if not isinstance(other, TaskDetail):
raise exc.NotImplementedError("Can only merge with other"
" task details")
if other is self:
return self
super(TaskDetail, self).merge(other, deep_copy=deep_copy)
if self.results != other.results:
self.results = other.results
return self
def copy(self):
"""Copies this task detail.
Creates a shallow copy of this task detail (any meta-data and
version information that this object maintains is shallow
copied via ``copy.copy``).
NOTE(harlowja): This copy does **not** perform ``copy.copy`` on
the ``results`` attribute of this object (before assigning to the
copy). Instead the current objects ``results`` attribute directly
becomes (via assignment) the copied objects ``results`` attribute.
See: https://bugs.launchpad.net/taskflow/+bug/1452978 for
what happens if this is copied at a deeper level (for example by
using ``copy.deepcopy`` or by using ``copy.copy``).
:returns: a new task detail
:rtype: :py:class:`.TaskDetail`
"""
clone = copy.copy(self)
clone.results = self.results
if self.meta:
clone.meta = self.meta.copy()
if self.version:
clone.version = copy.copy(self.version)
return clone
class RetryDetail(AtomDetail):
"""A retry detail (an atom detail typically associated with a |rt| atom).
.. |rt| replace:: :py:class:`~taskflow.retry.Retry`
"""
def __init__(self, name, uuid):
super(RetryDetail, self).__init__(name, uuid)
self.results = []
def reset(self, state):
"""Resets this retry detail and sets ``state`` attribute value.
This sets any previously added ``results`` back to an empty list
and resets the ``failure`` attribute back to ``None`` and sets the
state to the provided one, as well as setting this atom
details ``intention`` attribute to ``EXECUTE``.
"""
self.results = []
self.failure = None
self.state = state
self.intention = states.EXECUTE
def copy(self):
"""Copies this retry detail.
Creates a shallow copy of this retry detail (any meta-data and
version information that this object maintains is shallow
copied via ``copy.copy``).
NOTE(harlowja): This copy does **not** copy
the incoming objects ``results`` attribute. Instead this
objects ``results`` attribute list is iterated over and a new list
is constructed with each ``(data, failures)`` element in that list
having its ``failures`` (a dictionary of each named
:py:class:`~taskflow.types.failure.Failure` object that
occured) copied but its ``data`` is left untouched. After
this is done that new list becomes (via assignment) the cloned
objects ``results`` attribute.
See: https://bugs.launchpad.net/taskflow/+bug/1452978 for
what happens if the ``data`` in ``results`` is copied at a
deeper level (for example by using ``copy.deepcopy`` or by
using ``copy.copy``).
:returns: a new retry detail
:rtype: :py:class:`.RetryDetail`
"""
clone = copy.copy(self)
results = []
# NOTE(imelnikov): we can't just deep copy Failures, as they
# contain tracebacks, which are not copyable.
for (data, failures) in self.results:
copied_failures = {}
for (key, failure) in six.iteritems(failures):
copied_failures[key] = failure
results.append((data, copied_failures))
clone.results = results
if self.meta:
clone.meta = self.meta.copy()
if self.version:
clone.version = copy.copy(self.version)
return clone
@property
def last_results(self):
"""The last result that was produced."""
try:
return self.results[-1][0]
except IndexError:
exc.raise_with_cause(exc.NotFound, "Last results not found")
@property
def last_failures(self):
"""The last failure dictionary that was produced.
NOTE(harlowja): This is **not** the same as the
local ``failure`` attribute as the obtained failure dictionary in
the ``results`` attribute (which is what this returns) is from
associated atom failures (which is different from the directly
related failure of the retry unit associated with this
atom detail).
"""
try:
return self.results[-1][1]
except IndexError:
exc.raise_with_cause(exc.NotFound, "Last failures not found")
def put(self, state, result):
"""Puts a result (acquired in the given state) into this detail.
If the result is a :py:class:`~taskflow.types.failure.Failure` object
then the ``failure`` attribute will be set; if the result is not a
:py:class:`~taskflow.types.failure.Failure` object then the
``results`` attribute will be appended to (and the ``failure``
attribute will be set to ``None``). In either case the ``state``
attribute will be set to the provided state.
"""
# Do not clean retry history (only on reset does this happen).
self.state = state
if self._was_failure(state, result):
self.failure = result
else:
self.results.append((result, {}))
self.failure = None
return True
@classmethod
def from_dict(cls, data):
"""Translates the given ``dict`` into an instance of this class."""
def decode_results(results):
if not results:
return []
new_results = []
for (data, failures) in results:
new_failures = {}
for (key, data) in six.iteritems(failures):
new_failures[key] = ft.Failure.from_dict(data)
new_results.append((data, new_failures))
return new_results
obj = super(RetryDetail, cls).from_dict(data)
obj.results = decode_results(obj.results)
return obj
def to_dict(self):
"""Translates the internal state of this object to a ``dict``."""
def encode_results(results):
if not results:
return []
new_results = []
for (data, failures) in results:
new_failures = {}
for (key, failure) in six.iteritems(failures):
new_failures[key] = failure.to_dict()
new_results.append((data, new_failures))
return new_results
base = super(RetryDetail, self).to_dict()
base['results'] = encode_results(base.get('results'))
return base
def merge(self, other, deep_copy=False):
"""Merges the current retry detail with the given one.
NOTE(harlowja): This merge does **not** deep copy
the incoming objects ``results`` attribute (if it differs). Instead
the incoming objects ``results`` attribute list is **always** iterated
over and a new list is constructed with
each ``(data, failures)`` element in that list having
its ``failures`` (a dictionary of each named
:py:class:`~taskflow.types.failure.Failure` objects that
occurred) copied but its ``data`` is left untouched. After
this is done that new list becomes (via assignment) this
objects ``results`` attribute. Also note that if the provided object
is this object itself then **no** merging is done.
See: https://bugs.launchpad.net/taskflow/+bug/1452978 for
what happens if the ``data`` in ``results`` is copied at a
deeper level (for example by using ``copy.deepcopy`` or by
using ``copy.copy``).
:returns: this retry detail (freshly merged with the incoming object)
:rtype: :py:class:`.RetryDetail`
"""
if not isinstance(other, RetryDetail):
raise exc.NotImplementedError("Can only merge with other"
" retry details")
if other is self:
return self
super(RetryDetail, self).merge(other, deep_copy=deep_copy)
results = []
# NOTE(imelnikov): we can't just deep copy Failures, as they
# contain tracebacks, which are not copyable.
for (data, failures) in other.results:
copied_failures = {}
for (key, failure) in six.iteritems(failures):
if deep_copy:
copied_failures[key] = failure.copy()
else:
copied_failures[key] = failure
results.append((data, copied_failures))
self.results = results
return self
_DETAIL_TO_NAME = {
RetryDetail: 'RETRY_DETAIL',
TaskDetail: 'TASK_DETAIL',
}
_NAME_TO_DETAIL = dict((name, cls)
for (cls, name) in six.iteritems(_DETAIL_TO_NAME))
ATOM_TYPES = list(six.iterkeys(_NAME_TO_DETAIL))
def atom_detail_class(atom_type):
try:
return _NAME_TO_DETAIL[atom_type]
except KeyError:
raise TypeError("Unknown atom type '%s'" % (atom_type))
def atom_detail_type(atom_detail):
try:
return _DETAIL_TO_NAME[type(atom_detail)]
except KeyError:
raise TypeError("Unknown atom '%s' (%s)"
% (atom_detail, type(atom_detail)))

28
taskflow/persistence/path_based.py
View File

@ -19,7 +19,7 @@ import six
from taskflow import exceptions as exc
from taskflow.persistence import base
from taskflow.persistence import logbook
from taskflow.persistence import models
@six.add_metaclass(abc.ABCMeta)
@ -60,23 +60,23 @@ class PathBasedConnection(base.Connection):
@staticmethod
def _serialize(obj):
if isinstance(obj, logbook.LogBook):
if isinstance(obj, models.LogBook):
return obj.to_dict(marshal_time=True)
elif isinstance(obj, logbook.FlowDetail):
elif isinstance(obj, models.FlowDetail):
return obj.to_dict()
elif isinstance(obj, logbook.AtomDetail):
elif isinstance(obj, models.AtomDetail):
return base._format_atom(obj)
else:
raise exc.StorageFailure("Invalid storage class %s" % type(obj))
@staticmethod
def _deserialize(cls, data):
if issubclass(cls, logbook.LogBook):
if issubclass(cls, models.LogBook):
return cls.from_dict(data, unmarshal_time=True)
elif issubclass(cls, logbook.FlowDetail):
elif issubclass(cls, models.FlowDetail):
return cls.from_dict(data)
elif issubclass(cls, logbook.AtomDetail):
atom_class = logbook.atom_detail_class(data['type'])
elif issubclass(cls, models.AtomDetail):
atom_class = models.atom_detail_class(data['type'])
return atom_class.from_dict(data['atom'])
else:
raise exc.StorageFailure("Invalid storage class %s" % cls)
@ -130,11 +130,11 @@ class PathBasedConnection(base.Connection):
"""Context manager that yields a transaction"""
def _get_obj_path(self, obj):
if isinstance(obj, logbook.LogBook):
if isinstance(obj, models.LogBook):
path = self.book_path
elif isinstance(obj, logbook.FlowDetail):
elif isinstance(obj, models.FlowDetail):
path = self.flow_path
elif isinstance(obj, logbook.AtomDetail):
elif isinstance(obj, models.AtomDetail):
path = self.atom_path
else:
raise exc.StorageFailure("Invalid storage class %s" % type(obj))
@ -159,7 +159,7 @@ class PathBasedConnection(base.Connection):
def get_logbook(self, book_uuid, lazy=False):
book_path = self._join_path(self.book_path, book_uuid)
book_data = self._get_item(book_path)
book = self._deserialize(logbook.LogBook, book_data)
book = self._deserialize(models.LogBook, book_data)
if not lazy:
for flow_details in self.get_flows_for_book(book_uuid):
book.add(flow_details)
@ -185,7 +185,7 @@ class PathBasedConnection(base.Connection):
def get_flow_details(self, flow_uuid, lazy=False):
flow_path = self._join_path(self.flow_path, flow_uuid)
flow_data = self._get_item(flow_path)
flow_details = self._deserialize(logbook.FlowDetail, flow_data)
flow_details = self._deserialize(models.FlowDetail, flow_data)
if not lazy:
for atom_details in self.get_atoms_for_flow(flow_uuid):
flow_details.add(atom_details)
@ -216,7 +216,7 @@ class PathBasedConnection(base.Connection):
def get_atom_details(self, atom_uuid):
atom_path = self._join_path(self.atom_path, atom_uuid)
atom_data = self._get_item(atom_path)
return self._deserialize(logbook.AtomDetail, atom_data)
return self._deserialize(models.AtomDetail, atom_data)
def update_atom_details(self, atom_detail, ignore_missing=False):
with self._transaction() as transaction:

26
taskflow/storage.py
View File

@ -24,7 +24,7 @@ import six
from taskflow import exceptions
from taskflow import logging
from taskflow.persistence.backends import impl_memory
from taskflow.persistence import logbook
from taskflow.persistence import models
from taskflow import retry
from taskflow import states
from taskflow import task
@ -153,8 +153,8 @@ class Storage(object):
self._injected_args = {}
self._lock = fasteners.ReaderWriterLock()
self._ensure_matchers = [
((task.BaseTask,), (logbook.TaskDetail, 'Task')),
((retry.Retry,), (logbook.RetryDetail, 'Retry')),
((task.BaseTask,), (models.TaskDetail, 'Task')),
((retry.Retry,), (models.RetryDetail, 'Retry')),
]
if scope_fetcher is None:
scope_fetcher = lambda atom_name: None
@ -171,7 +171,7 @@ class Storage(object):
for ad in self._flowdetail)
try:
source, _clone = self._atomdetail_by_name(
self.injector_name, expected_type=logbook.TaskDetail)
self.injector_name, expected_type=models.TaskDetail)
except exceptions.NotFound:
pass
else:
@ -399,7 +399,7 @@ class Storage(object):
else:
update_with[META_PROGRESS_DETAILS] = None
self._update_atom_metadata(task_name, update_with,
expected_type=logbook.TaskDetail)
expected_type=models.TaskDetail)
@fasteners.read_locked
def get_task_progress(self, task_name):
@ -409,7 +409,7 @@ class Storage(object):
:returns: current task progress value
"""
source, _clone = self._atomdetail_by_name(
task_name, expected_type=logbook.TaskDetail)
task_name, expected_type=models.TaskDetail)
try:
return source.meta[META_PROGRESS]
except KeyError:
@ -424,7 +424,7 @@ class Storage(object):
dict
"""
source, _clone = self._atomdetail_by_name(
task_name, expected_type=logbook.TaskDetail)
task_name, expected_type=models.TaskDetail)
try:
return source.meta[META_PROGRESS_DETAILS]
except KeyError:
@ -468,7 +468,7 @@ class Storage(object):
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=logbook.RetryDetail, clone=True)
retry_name, expected_type=models.RetryDetail, clone=True)
try:
failures = clone.last_failures
except exceptions.NotFound:
@ -485,7 +485,7 @@ class Storage(object):
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=logbook.RetryDetail, clone=True)
retry_name, expected_type=models.RetryDetail, clone=True)
clone.state = state
clone.results = []
self._with_connection(self._save_atom_detail, source, clone)
@ -625,7 +625,7 @@ class Storage(object):
try:
source, clone = self._atomdetail_by_name(
self.injector_name,
expected_type=logbook.TaskDetail,
expected_type=models.TaskDetail,
clone=True)
except exceptions.NotFound:
# Ensure we have our special task detail...
@ -633,7 +633,7 @@ class Storage(object):
# TODO(harlowja): get this removed when
# https://review.openstack.org/#/c/165645/ merges.
source = self._create_atom_detail(self.injector_name,
logbook.TaskDetail,
models.TaskDetail,
atom_state=None)
fd_source, fd_clone = self._fetch_flowdetail(clone=True)
fd_clone.add(source)
@ -974,7 +974,7 @@ class Storage(object):
def get_retry_history(self, retry_name):
"""Fetch a single retrys history."""
source, _clone = self._atomdetail_by_name(
retry_name, expected_type=logbook.RetryDetail)
retry_name, expected_type=models.RetryDetail)
return self._translate_into_history(source)
@fasteners.read_locked
@ -982,7 +982,7 @@ class Storage(object):
"""Fetch all retrys histories."""
histories = []
for ad in self._flowdetail:
if isinstance(ad, logbook.RetryDetail):
if isinstance(ad, models.RetryDetail):
histories.append((ad.name,
self._translate_into_history(ad)))
return histories

102
taskflow/tests/unit/persistence/base.py
View File

@ -19,7 +19,7 @@ import contextlib
from oslo_utils import uuidutils
from taskflow import exceptions as exc
from taskflow.persistence import logbook
from taskflow.persistence import models
from taskflow import states
from taskflow.types import failure
@ -31,15 +31,15 @@ class PersistenceTestMixin(object):
def test_task_detail_update_not_existing(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
td = logbook.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
td = models.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
fd.add(td)
with contextlib.closing(self._get_connection()) as conn:
conn.save_logbook(lb)
td2 = logbook.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
td2 = models.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
fd.add(td2)
with contextlib.closing(self._get_connection()) as conn:
conn.update_flow_details(fd)
@ -53,13 +53,13 @@ class PersistenceTestMixin(object):
def test_flow_detail_update_not_existing(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
with contextlib.closing(self._get_connection()) as conn:
conn.save_logbook(lb)
fd2 = logbook.FlowDetail('test-2', uuid=uuidutils.generate_uuid())
fd2 = models.FlowDetail('test-2', uuid=uuidutils.generate_uuid())
lb.add(fd2)
with contextlib.closing(self._get_connection()) as conn:
conn.save_logbook(lb)
@ -73,7 +73,7 @@ class PersistenceTestMixin(object):
lb_id = uuidutils.generate_uuid()
lb_meta = {'1': 2}
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
lb = models.LogBook(name=lb_name, uuid=lb_id)
lb.meta = lb_meta
# Should not already exist
@ -94,8 +94,8 @@ class PersistenceTestMixin(object):
def test_flow_detail_save(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
# Ensure we can't save it since its owning logbook hasn't been
@ -113,8 +113,8 @@ class PersistenceTestMixin(object):
def test_flow_detail_meta_update(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
fd.meta = {'test': 42}
lb.add(fd)
@ -133,9 +133,9 @@ class PersistenceTestMixin(object):
def test_flow_detail_lazy_fetch(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
td = logbook.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
td = models.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
td.version = '4.2'
fd.add(td)
lb.add(fd)
@ -149,10 +149,10 @@ class PersistenceTestMixin(object):
def test_task_detail_save(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
td = logbook.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
td = models.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
fd.add(td)
# Ensure we can't save it since its owning logbook hasn't been
@ -171,10 +171,10 @@ class PersistenceTestMixin(object):
def test_task_detail_meta_update(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
td = logbook.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
td = models.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
td.meta = {'test': 42}
fd.add(td)
@ -192,15 +192,15 @@ class PersistenceTestMixin(object):
fd2 = lb2.find(fd.uuid)
td2 = fd2.find(td.uuid)
self.assertEqual(td2.meta.get('test'), 43)
self.assertIsInstance(td2, logbook.TaskDetail)
self.assertIsInstance(td2, models.TaskDetail)
def test_task_detail_with_failure(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
td = logbook.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
td = models.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
try:
raise RuntimeError('Woot!')
@ -222,18 +222,18 @@ class PersistenceTestMixin(object):
self.assertEqual(td2.failure.exception_str, 'Woot!')
self.assertIs(td2.failure.check(RuntimeError), RuntimeError)
self.assertEqual(td2.failure.traceback_str, td.failure.traceback_str)
self.assertIsInstance(td2, logbook.TaskDetail)
self.assertIsInstance(td2, models.TaskDetail)
def test_logbook_merge_flow_detail(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
with contextlib.closing(self._get_connection()) as conn:
conn.save_logbook(lb)
lb2 = logbook.LogBook(name=lb_name, uuid=lb_id)
fd2 = logbook.FlowDetail('test2', uuid=uuidutils.generate_uuid())
lb2 = models.LogBook(name=lb_name, uuid=lb_id)
fd2 = models.FlowDetail('test2', uuid=uuidutils.generate_uuid())
lb2.add(fd2)
with contextlib.closing(self._get_connection()) as conn:
conn.save_logbook(lb2)
@ -244,8 +244,8 @@ class PersistenceTestMixin(object):
def test_logbook_add_flow_detail(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
with contextlib.closing(self._get_connection()) as conn:
conn.save_logbook(lb)
@ -258,8 +258,8 @@ class PersistenceTestMixin(object):
def test_logbook_lazy_fetch(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
with contextlib.closing(self._get_connection()) as conn:
conn.save_logbook(lb)
@ -271,9 +271,9 @@ class PersistenceTestMixin(object):
def test_logbook_add_task_detail(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
td = logbook.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
td = models.TaskDetail("detail-1", uuid=uuidutils.generate_uuid())
td.version = '4.2'
fd.add(td)
lb.add(fd)
@ -298,7 +298,7 @@ class PersistenceTestMixin(object):
def test_logbook_delete(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
lb = models.LogBook(name=lb_name, uuid=lb_id)
with contextlib.closing(self._get_connection()) as conn:
self.assertRaises(exc.NotFound, conn.destroy_logbook, lb_id)
with contextlib.closing(self._get_connection()) as conn:
@ -313,10 +313,10 @@ class PersistenceTestMixin(object):
def test_task_detail_retry_type_(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
rd = logbook.RetryDetail("detail-1", uuid=uuidutils.generate_uuid())
rd = models.RetryDetail("detail-1", uuid=uuidutils.generate_uuid())
rd.intention = states.REVERT
fd.add(rd)
@ -330,15 +330,15 @@ class PersistenceTestMixin(object):
fd2 = lb2.find(fd.uuid)
rd2 = fd2.find(rd.uuid)
self.assertEqual(rd2.intention, states.REVERT)
self.assertIsInstance(rd2, logbook.RetryDetail)
self.assertIsInstance(rd2, models.RetryDetail)
def test_retry_detail_save_with_task_failure(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
rd = logbook.RetryDetail("retry-1", uuid=uuidutils.generate_uuid())
rd = models.RetryDetail("retry-1", uuid=uuidutils.generate_uuid())
fail = failure.Failure.from_exception(RuntimeError('fail'))
rd.results.append((42, {'some-task': fail}))
fd.add(rd)
@ -354,7 +354,7 @@ class PersistenceTestMixin(object):
lb2 = conn.get_logbook(lb_id)
fd2 = lb2.find(fd.uuid)
rd2 = fd2.find(rd.uuid)
self.assertIsInstance(rd2, logbook.RetryDetail)
self.assertIsInstance(rd2, models.RetryDetail)
fail2 = rd2.results[0][1].get('some-task')
self.assertIsInstance(fail2, failure.Failure)
self.assertTrue(fail.matches(fail2))
@ -362,10 +362,10 @@ class PersistenceTestMixin(object):
def test_retry_detail_save_intention(self):
lb_id = uuidutils.generate_uuid()
lb_name = 'lb-%s' % (lb_id)
lb = logbook.LogBook(name=lb_name, uuid=lb_id)
fd = logbook.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb = models.LogBook(name=lb_name, uuid=lb_id)
fd = models.FlowDetail('test', uuid=uuidutils.generate_uuid())
lb.add(fd)
rd = logbook.RetryDetail("retry-1", uuid=uuidutils.generate_uuid())
rd = models.RetryDetail("retry-1", uuid=uuidutils.generate_uuid())
fd.add(rd)
# save it
@ -385,4 +385,4 @@ class PersistenceTestMixin(object):
fd2 = lb2.find(fd.uuid)
rd2 = fd2.find(rd.uuid)
self.assertEqual(rd2.intention, states.REVERT)
self.assertIsInstance(rd2, logbook.RetryDetail)
self.assertIsInstance(rd2, models.RetryDetail)

4
taskflow/tests/unit/test_engines.py
View File

@ -26,7 +26,7 @@ from taskflow import exceptions as exc
from taskflow.patterns import graph_flow as gf
from taskflow.patterns import linear_flow as lf
from taskflow.patterns import unordered_flow as uf
from taskflow.persistence import logbook
from taskflow.persistence import models
from taskflow import states
from taskflow import task
from taskflow import test
@ -493,7 +493,7 @@ class EngineParallelFlowTest(utils.EngineTestBase):
# Create FlowDetail as if we already run task1
lb, fd = p_utils.temporary_flow_detail(self.backend)
td = logbook.TaskDetail(name='task1', uuid='42')
td = models.TaskDetail(name='task1', uuid='42')
td.state = states.SUCCESS
td.results = 17
fd.add(td)

10
taskflow/tests/unit/test_storage.py
View File

@ -21,7 +21,7 @@ from oslo_utils import uuidutils
from taskflow import exceptions
from taskflow.persistence import backends
from taskflow.persistence import logbook
from taskflow.persistence import models
from taskflow import states
from taskflow import storage
from taskflow import test
@ -61,7 +61,7 @@ class StorageTestMixin(object):
self.assertTrue(uuidutils.is_uuid_like(s.get_atom_uuid('my_task')))
def test_flow_name_and_uuid(self):
flow_detail = logbook.FlowDetail(name='test-fd', uuid='aaaa')
flow_detail = models.FlowDetail(name='test-fd', uuid='aaaa')
s = self._get_storage(flow_detail)
self.assertEqual(s.flow_name, 'test-fd')
self.assertEqual(s.flow_uuid, 'aaaa')
@ -97,14 +97,14 @@ class StorageTestMixin(object):
def test_get_without_save(self):
_lb, flow_detail = p_utils.temporary_flow_detail(self.backend)
td = logbook.TaskDetail(name='my_task', uuid='42')
td = models.TaskDetail(name='my_task', uuid='42')
flow_detail.add(td)
s = self._get_storage(flow_detail)
self.assertEqual('42', s.get_atom_uuid('my_task'))
def test_ensure_existing_task(self):
_lb, flow_detail = p_utils.temporary_flow_detail(self.backend)
td = logbook.TaskDetail(name='my_task', uuid='42')
td = models.TaskDetail(name='my_task', uuid='42')
flow_detail.add(td)
s = self._get_storage(flow_detail)
s.ensure_atom(test_utils.NoopTask('my_task'))
@ -523,7 +523,7 @@ class StorageTestMixin(object):
def test_logbook_get_unknown_atom_type(self):
self.assertRaisesRegexp(TypeError,
'Unknown atom',
logbook.atom_detail_class, 'some_detail')
models.atom_detail_class, 'some_detail')
def test_save_task_intention(self):
s = self._get_storage()

10
taskflow/utils/persistence_utils.py
View File

@ -21,7 +21,7 @@ from oslo_utils import timeutils
from oslo_utils import uuidutils
from taskflow import logging
from taskflow.persistence import logbook
from taskflow.persistence import models
from taskflow.utils import misc
LOG = logging.getLogger(__name__)
@ -33,7 +33,7 @@ def temporary_log_book(backend=None):
Mainly useful for tests and other use cases where a temporary logbook
is needed for a short-period of time.
"""
book = logbook.LogBook('tmp')
book = models.LogBook('tmp')
if backend is not None:
with contextlib.closing(backend.get_connection()) as conn:
conn.save_logbook(book)
@ -48,7 +48,7 @@ def temporary_flow_detail(backend=None):
"""
flow_id = uuidutils.generate_uuid()
book = temporary_log_book(backend)
book.add(logbook.FlowDetail(name='tmp-flow-detail', uuid=flow_id))
book.add(models.FlowDetail(name='tmp-flow-detail', uuid=flow_id))
if backend is not None:
with contextlib.closing(backend.get_connection()) as conn:
conn.save_logbook(book)
@ -77,7 +77,7 @@ def create_flow_detail(flow, book=None, backend=None, meta=None):
LOG.warn("No name provided for flow %s (id %s)", flow, flow_id)
flow_name = flow_id
flow_detail = logbook.FlowDetail(name=flow_name, uuid=flow_id)
flow_detail = models.FlowDetail(name=flow_name, uuid=flow_id)
if meta is not None:
if flow_detail.meta is None:
flow_detail.meta = {}
@ -130,7 +130,7 @@ def _format_shared(obj, indent):
def pformat_atom_detail(atom_detail, indent=0):
"""Pretty formats a atom detail."""
detail_type = logbook.atom_detail_type(atom_detail)
detail_type = models.atom_detail_type(atom_detail)
lines = ["%s%s: '%s'" % (" " * (indent), detail_type, atom_detail.name)]
lines.extend(_format_shared(atom_detail, indent=indent + 1))
lines.append("%s- version = %s"