def setUp(self):
setup.placelessSetUp()
provideAdapter(ZodbObjectHistory)
tree = OOBTree()
tree[1] = 42
tree[2] = 23
tree[3] = 17
state = tree.__getstate__()
self.state = EmptyOOBTreeState(None, state, None)
def setUp(self):
setup.placelessSetUp()
provideAdapter(ZodbObjectHistory)
tree = OOBTree()
tree[1] = 42
tree[2] = 23
tree[3] = 17
state = tree.__getstate__()
self.state = EmptyOOBTreeState(None, state, None)
def test_normal(self):
from BTrees.OOBTree import OOBTree
tree = OOBTree()
for i in range(31):
tree[i] = 2 * i
state = tree.__getstate__()
self.assertEqual(len(state), 2)
self.assertEqual(len(state[0]), 3)
self.assertEqual(state[0][1], 15)
self._callFUT(tree) #noraise
def test_normal(self):
from BTrees.OOBTree import OOBTree
tree = OOBTree()
for i in range(31):
tree[i] = 2*i
state = tree.__getstate__()
self.assertEqual(len(state), 2)
self.assertEqual(len(state[0]), 3)
self.assertEqual(state[0][1], 15)
self._callFUT(tree) #noraise
def _constructAnnotatedHistory(self, max=10):
"""Reconstruct historical revisions of archetypes objects
Merges revisions to self with revisions to archetypes-related items
in __annotations__. Yields at most max recent revisions.
"""
# All relevant historical states by transaction id
# For every tid, keep a dict with object revisions, keyed on annotation
# id, or None for self and '__annotations__' for the ann OOBTree
# Initialize with self revisions
history = dict([(tid, {None: rev})
for (tid, rev) in _objectRevisions(self, max)])
if not getattr(self, '__annotations__', None):
# No annotations, just return the history we have for self
# Note that if this object had __annotations__ in a past
# transaction they will be ignored! Working around this is a
# YAGNI I think though.
for tid in sorted(history.keys()):
yield history[tid][None]
return
# Now find all __annotation__ revisions, and the annotation keys
# used in those.
annotation_key_objects = {}
isatkey = lambda k, aak=AT_ANN_KEYS: filter(k.startswith, aak)
# Loop over max revisions of the __annotations__ object to retrieve
# all keys (and more importantly, their objects so we can get
# revisions)
for tid, rev in _objectRevisions(self.__annotations__, max):
history.setdefault(tid, {})['__annotations__'] = rev
revision = rev['object']
for key in itertools.ifilter(isatkey, revision.iterkeys()):
if not hasattr(revision[key], '_p_jar'):
continue # Not persistent
if key not in annotation_key_objects:
annotation_key_objects[key] = revision[key]
# For all annotation keys, get their revisions
for key, obj in annotation_key_objects.iteritems():
for tid, rev in _objectRevisions(obj, max):
history.setdefault(tid, {})[key] = rev
del annotation_key_objects
# Now we merge the annotation and object revisions into one for each
# transaction id, and yield the results
tids = sorted(history.iterkeys(), reverse=True)
def find_revision(tids, key):
"""First revision of key in a series of tids"""
has_revision = lambda t, h=history, k=key: k in h[t]
next_tid = itertools.ifilter(has_revision, tids).next()
return history[next_tid][key]
for i, tid in enumerate(tids[:max]):
revision = find_revision(tids[i:], None)
obj = revision['object']
# Track size to maintain correct metadata
size = revision['size']
anns_rev = find_revision(tids[i:], '__annotations__')
size += anns_rev['size']
anns = anns_rev['object']
# We use a temporary OOBTree to avoid _p_jar complaints from the
# transaction machinery
tempbtree = OOBTree()
tempbtree.__setstate__(anns.__getstate__())
# Find annotation revisions and insert
for key in itertools.ifilter(isatkey, tempbtree.iterkeys()):
if not hasattr(tempbtree[key], '_p_jar'):
continue # Not persistent
value_rev = find_revision(tids[i:], key)
size += value_rev['size']
tempbtree[key] = value_rev['object']
# Now transfer the tembtree state over to anns, effectively
# bypassing the transaction registry while maintaining BTree
# integrity
anns.__setstate__(tempbtree.__getstate__())
anns._p_changed = 0
del tempbtree
# Do a similar hack to set anns on the main object
state = obj.__getstate__()
state['__annotations__'] = anns
obj.__setstate__(state)
obj._p_changed = 0
# Update revision metadata if needed
if revision['tid'] != tid:
# any other revision will do; only size and object are unique
revision = history[tid].values()[0].copy()
revision['object'] = obj
# Correct size based on merged records
revision['size'] = size
# clean up as we go
del history[tid]
yield revision
def __getstate__(self):
return Persistent.__getstate__(self), OOBTree.__getstate__(self)
def __getstate__(self):
return Persistent.__getstate__(self), OOBTree.__getstate__(self)
def _constructAnnotatedHistory(self, max=10):
"""Reconstruct historical revisions of archetypes objects
Merges revisions to self with revisions to archetypes-related items
in __annotations__. Yields at most max recent revisions.
"""
# All relevant historical states by transaction id
# For every tid, keep a dict with object revisions, keyed on annotation
# id, or None for self and '__annotations__' for the ann OOBTree
# Initialize with self revisions
history = dict([(tid, {None: rev})
for (tid, rev) in _objectRevisions(self, max)])
if not getattr(self, '__annotations__', None):
# No annotations, just return the history we have for self
# Note that if this object had __annotations__ in a past
# transaction they will be ignored! Working around this is a
# YAGNI I think though.
for tid in sorted(history.keys()):
yield history[tid][None]
return
# Now find all __annotation__ revisions, and the annotation keys
# used in those.
annotation_key_objects = {}
isatkey = lambda k, aak=AT_ANN_KEYS: filter(k.startswith, aak)
# Loop over max revisions of the __annotations__ object to retrieve
# all keys (and more importantly, their objects so we can get revisions)
for tid, rev in _objectRevisions(self.__annotations__, max):
history.setdefault(tid, {})['__annotations__'] = rev
revision = rev['object']
for key in itertools.ifilter(isatkey, revision.iterkeys()):
if not hasattr(revision[key], '_p_jar'):
continue # Not persistent
if key not in annotation_key_objects:
annotation_key_objects[key] = revision[key]
# For all annotation keys, get their revisions
for key, obj in annotation_key_objects.iteritems():
for tid, rev in _objectRevisions(obj, max):
history.setdefault(tid, {})[key] = rev
del annotation_key_objects
# Now we merge the annotation and object revisions into one for each
# transaction id, and yield the results
tids = sorted(history.iterkeys(), reverse=True)
def find_revision(tids, key):
# First revision of key in a series of tids.
has_revision = lambda t, h=history, k=key: k in h[t]
next_tid = itertools.ifilter(has_revision, tids).next()
return history[next_tid][key]
for i, tid in enumerate(tids[:max]):
revision = find_revision(tids[i:], None)
obj = revision['object']
# Track size to maintain correct metadata
size = revision['size']
anns_rev = find_revision(tids[i:], '__annotations__')
size += anns_rev['size']
anns = anns_rev['object']
# We use a temporary OOBTree to avoid _p_jar complaints from the
# transaction machinery
tempbtree = OOBTree()
tempbtree.__setstate__(anns.__getstate__())
# Find annotation revisions and insert
for key in itertools.ifilter(isatkey, tempbtree.iterkeys()):
if not hasattr(tempbtree[key], '_p_jar'):
continue # Not persistent
value_rev = find_revision(tids[i:], key)
size += value_rev['size']
tempbtree[key] = value_rev['object']
# Now transfer the tembtree state over to anns, effectively
# bypassing the transaction registry while maintaining BTree
# integrity
anns.__setstate__(tempbtree.__getstate__())
anns._p_changed = 0
del tempbtree
# Do a similar hack to set anns on the main object
state = obj.__getstate__()
state['__annotations__'] = anns
obj.__setstate__(state)
obj._p_changed = 0
# Update revision metadata if needed
if revision['tid'] != tid:
# any other revision will do; only size and object are unique
revision = history[tid].values()[0].copy()
revision['object'] = obj
# Correct size based on merged records
revision['size'] = size
# clean up as we go
del history[tid]
yield revision
