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# Copyright (C) 2007-2010 Canonical Ltd
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version.
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the Free Software
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# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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from bzrlib.symbol_versioning import deprecated_function, deprecated_in
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STEP_UNIQUE_SEARCHER_EVERY = 5
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# DIAGRAM of terminology
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# In this diagram, relative to G and H:
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# A, B, C, D, E are common ancestors.
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# C, D and E are border ancestors, because each has a non-common descendant.
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# D and E are least common ancestors because none of their descendants are
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# C is not a least common ancestor because its descendant, E, is a common
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# The find_unique_lca algorithm will pick A in two steps:
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# 1. find_lca('G', 'H') => ['D', 'E']
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# 2. Since len(['D', 'E']) > 1, find_lca('D', 'E') => ['A']
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class DictParentsProvider(object):
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"""A parents provider for Graph objects."""
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def __init__(self, ancestry):
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self.ancestry = ancestry
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return 'DictParentsProvider(%r)' % self.ancestry
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def get_parent_map(self, keys):
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"""See StackedParentsProvider.get_parent_map"""
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ancestry = self.ancestry
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return dict((k, ancestry[k]) for k in keys if k in ancestry)
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@deprecated_function(deprecated_in((1, 16, 0)))
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def _StackedParentsProvider(*args, **kwargs):
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return StackedParentsProvider(*args, **kwargs)
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class StackedParentsProvider(object):
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"""A parents provider which stacks (or unions) multiple providers.
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The providers are queries in the order of the provided parent_providers.
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def __init__(self, parent_providers):
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self._parent_providers = parent_providers
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return "%s(%r)" % (self.__class__.__name__, self._parent_providers)
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def get_parent_map(self, keys):
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"""Get a mapping of keys => parents
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A dictionary is returned with an entry for each key present in this
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source. If this source doesn't have information about a key, it should
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[NULL_REVISION] is used as the parent of the first user-committed
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revision. Its parent list is empty.
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:param keys: An iterable returning keys to check (eg revision_ids)
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:return: A dictionary mapping each key to its parents
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for parents_provider in self._parent_providers:
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new_found = parents_provider.get_parent_map(remaining)
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found.update(new_found)
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remaining.difference_update(new_found)
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class CachingParentsProvider(object):
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"""A parents provider which will cache the revision => parents as a dict.
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This is useful for providers which have an expensive look up.
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Either a ParentsProvider or a get_parent_map-like callback may be
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supplied. If it provides extra un-asked-for parents, they will be cached,
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but filtered out of get_parent_map.
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The cache is enabled by default, but may be disabled and re-enabled.
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def __init__(self, parent_provider=None, get_parent_map=None):
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:param parent_provider: The ParentProvider to use. It or
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get_parent_map must be supplied.
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:param get_parent_map: The get_parent_map callback to use. It or
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parent_provider must be supplied.
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self._real_provider = parent_provider
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if get_parent_map is None:
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self._get_parent_map = self._real_provider.get_parent_map
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self._get_parent_map = get_parent_map
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self.enable_cache(True)
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return "%s(%r)" % (self.__class__.__name__, self._real_provider)
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def enable_cache(self, cache_misses=True):
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if self._cache is not None:
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raise AssertionError('Cache enabled when already enabled.')
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self._cache_misses = cache_misses
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self.missing_keys = set()
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def disable_cache(self):
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"""Disable and clear the cache."""
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self._cache_misses = None
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self.missing_keys = set()
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def get_cached_map(self):
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"""Return any cached get_parent_map values."""
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if self._cache is None:
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return dict(self._cache)
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def get_parent_map(self, keys):
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"""See StackedParentsProvider.get_parent_map."""
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cache = self._get_parent_map(keys)
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needed_revisions = set(key for key in keys if key not in cache)
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# Do not ask for negatively cached keys
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needed_revisions.difference_update(self.missing_keys)
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parent_map = self._get_parent_map(needed_revisions)
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cache.update(parent_map)
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if self._cache_misses:
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for key in needed_revisions:
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if key not in parent_map:
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self.note_missing_key(key)
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value = cache.get(key)
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if value is not None:
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def note_missing_key(self, key):
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"""Note that key is a missing key."""
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if self._cache_misses:
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self.missing_keys.add(key)
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"""Provide incremental access to revision graphs.
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This is the generic implementation; it is intended to be subclassed to
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specialize it for other repository types.
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def __init__(self, parents_provider):
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"""Construct a Graph that uses several graphs as its input
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This should not normally be invoked directly, because there may be
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specialized implementations for particular repository types. See
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Repository.get_graph().
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:param parents_provider: An object providing a get_parent_map call
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conforming to the behavior of
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StackedParentsProvider.get_parent_map.
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if getattr(parents_provider, 'get_parents', None) is not None:
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self.get_parents = parents_provider.get_parents
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if getattr(parents_provider, 'get_parent_map', None) is not None:
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self.get_parent_map = parents_provider.get_parent_map
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self._parents_provider = parents_provider
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return 'Graph(%r)' % self._parents_provider
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def find_lca(self, *revisions):
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"""Determine the lowest common ancestors of the provided revisions
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A lowest common ancestor is a common ancestor none of whose
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descendants are common ancestors. In graphs, unlike trees, there may
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be multiple lowest common ancestors.
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This algorithm has two phases. Phase 1 identifies border ancestors,
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and phase 2 filters border ancestors to determine lowest common
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In phase 1, border ancestors are identified, using a breadth-first
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search starting at the bottom of the graph. Searches are stopped
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whenever a node or one of its descendants is determined to be common
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In phase 2, the border ancestors are filtered to find the least
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common ancestors. This is done by searching the ancestries of each
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Phase 2 is perfomed on the principle that a border ancestor that is
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not an ancestor of any other border ancestor is a least common
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Searches are stopped when they find a node that is determined to be a
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common ancestor of all border ancestors, because this shows that it
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cannot be a descendant of any border ancestor.
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The scaling of this operation should be proportional to
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1. The number of uncommon ancestors
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2. The number of border ancestors
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3. The length of the shortest path between a border ancestor and an
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ancestor of all border ancestors.
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border_common, common, sides = self._find_border_ancestors(revisions)
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# We may have common ancestors that can be reached from each other.
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# - ask for the heads of them to filter it down to only ones that
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# cannot be reached from each other - phase 2.
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return self.heads(border_common)
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def find_difference(self, left_revision, right_revision):
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"""Determine the graph difference between two revisions"""
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border, common, searchers = self._find_border_ancestors(
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[left_revision, right_revision])
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self._search_for_extra_common(common, searchers)
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left = searchers[0].seen
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right = searchers[1].seen
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return (left.difference(right), right.difference(left))
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def find_distance_to_null(self, target_revision_id, known_revision_ids):
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"""Find the left-hand distance to the NULL_REVISION.
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(This can also be considered the revno of a branch at
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:param target_revision_id: A revision_id which we would like to know
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:param known_revision_ids: [(revision_id, revno)] A list of known
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revno, revision_id tuples. We'll use this to seed the search.
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# Map from revision_ids to a known value for their revno
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known_revnos = dict(known_revision_ids)
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cur_tip = target_revision_id
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NULL_REVISION = revision.NULL_REVISION
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known_revnos[NULL_REVISION] = 0
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searching_known_tips = list(known_revnos.keys())
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unknown_searched = {}
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while cur_tip not in known_revnos:
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unknown_searched[cur_tip] = num_steps
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to_search = set([cur_tip])
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to_search.update(searching_known_tips)
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parent_map = self.get_parent_map(to_search)
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parents = parent_map.get(cur_tip, None)
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if not parents: # An empty list or None is a ghost
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raise errors.GhostRevisionsHaveNoRevno(target_revision_id,
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for revision_id in searching_known_tips:
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parents = parent_map.get(revision_id, None)
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next_revno = known_revnos[revision_id] - 1
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if next in unknown_searched:
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# We have enough information to return a value right now
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return next_revno + unknown_searched[next]
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if next in known_revnos:
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known_revnos[next] = next_revno
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next_known_tips.append(next)
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searching_known_tips = next_known_tips
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# We reached a known revision, so just add in how many steps it took to
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return known_revnos[cur_tip] + num_steps
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def find_lefthand_distances(self, keys):
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"""Find the distance to null for all the keys in keys.
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:param keys: keys to lookup.
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:return: A dict key->distance for all of keys.
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# Optimisable by concurrent searching, but a random spread should get
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# some sort of hit rate.
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(key, self.find_distance_to_null(key, known_revnos)))
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except errors.GhostRevisionsHaveNoRevno:
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known_revnos.append((key, -1))
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return dict(known_revnos)
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def find_unique_ancestors(self, unique_revision, common_revisions):
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"""Find the unique ancestors for a revision versus others.
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This returns the ancestry of unique_revision, excluding all revisions
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in the ancestry of common_revisions. If unique_revision is in the
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ancestry, then the empty set will be returned.
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:param unique_revision: The revision_id whose ancestry we are
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XXX: Would this API be better if we allowed multiple revisions on
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:param common_revisions: Revision_ids of ancestries to exclude.
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:return: A set of revisions in the ancestry of unique_revision
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if unique_revision in common_revisions:
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# Algorithm description
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# 1) Walk backwards from the unique node and all common nodes.
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# 2) When a node is seen by both sides, stop searching it in the unique
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# walker, include it in the common walker.
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# 3) Stop searching when there are no nodes left for the unique walker.
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# At this point, you have a maximal set of unique nodes. Some of
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# them may actually be common, and you haven't reached them yet.
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# 4) Start new searchers for the unique nodes, seeded with the
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# information you have so far.
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# 5) Continue searching, stopping the common searches when the search
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# tip is an ancestor of all unique nodes.
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# 6) Aggregate together unique searchers when they are searching the
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# same tips. When all unique searchers are searching the same node,
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# stop move it to a single 'all_unique_searcher'.
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# 7) The 'all_unique_searcher' represents the very 'tip' of searching.
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# Most of the time this produces very little important information.
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# So don't step it as quickly as the other searchers.
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# 8) Search is done when all common searchers have completed.
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unique_searcher, common_searcher = self._find_initial_unique_nodes(
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[unique_revision], common_revisions)
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unique_nodes = unique_searcher.seen.difference(common_searcher.seen)
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(all_unique_searcher,
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unique_tip_searchers) = self._make_unique_searchers(unique_nodes,
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unique_searcher, common_searcher)
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self._refine_unique_nodes(unique_searcher, all_unique_searcher,
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unique_tip_searchers, common_searcher)
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true_unique_nodes = unique_nodes.difference(common_searcher.seen)
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if 'graph' in debug.debug_flags:
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trace.mutter('Found %d truly unique nodes out of %d',
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len(true_unique_nodes), len(unique_nodes))
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return true_unique_nodes
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def _find_initial_unique_nodes(self, unique_revisions, common_revisions):
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"""Steps 1-3 of find_unique_ancestors.
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Find the maximal set of unique nodes. Some of these might actually
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still be common, but we are sure that there are no other unique nodes.
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:return: (unique_searcher, common_searcher)
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unique_searcher = self._make_breadth_first_searcher(unique_revisions)
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# we know that unique_revisions aren't in common_revisions, so skip
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unique_searcher.next()
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common_searcher = self._make_breadth_first_searcher(common_revisions)
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# As long as we are still finding unique nodes, keep searching
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while unique_searcher._next_query:
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next_unique_nodes = set(unique_searcher.step())
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next_common_nodes = set(common_searcher.step())
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# Check if either searcher encounters new nodes seen by the other
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unique_are_common_nodes = next_unique_nodes.intersection(
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common_searcher.seen)
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unique_are_common_nodes.update(
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next_common_nodes.intersection(unique_searcher.seen))
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if unique_are_common_nodes:
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ancestors = unique_searcher.find_seen_ancestors(
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unique_are_common_nodes)
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# TODO: This is a bit overboard, we only really care about
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# the ancestors of the tips because the rest we
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# already know. This is *correct* but causes us to
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# search too much ancestry.
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ancestors.update(common_searcher.find_seen_ancestors(ancestors))
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unique_searcher.stop_searching_any(ancestors)
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common_searcher.start_searching(ancestors)
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return unique_searcher, common_searcher
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def _make_unique_searchers(self, unique_nodes, unique_searcher,
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"""Create a searcher for all the unique search tips (step 4).
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As a side effect, the common_searcher will stop searching any nodes
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that are ancestors of the unique searcher tips.
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:return: (all_unique_searcher, unique_tip_searchers)
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unique_tips = self._remove_simple_descendants(unique_nodes,
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self.get_parent_map(unique_nodes))
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if len(unique_tips) == 1:
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unique_tip_searchers = []
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ancestor_all_unique = unique_searcher.find_seen_ancestors(unique_tips)
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unique_tip_searchers = []
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for tip in unique_tips:
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revs_to_search = unique_searcher.find_seen_ancestors([tip])
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revs_to_search.update(
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common_searcher.find_seen_ancestors(revs_to_search))
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searcher = self._make_breadth_first_searcher(revs_to_search)
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# We don't care about the starting nodes.
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searcher._label = tip
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unique_tip_searchers.append(searcher)
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ancestor_all_unique = None
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for searcher in unique_tip_searchers:
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if ancestor_all_unique is None:
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ancestor_all_unique = set(searcher.seen)
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ancestor_all_unique = ancestor_all_unique.intersection(
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# Collapse all the common nodes into a single searcher
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all_unique_searcher = self._make_breadth_first_searcher(
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if ancestor_all_unique:
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# We've seen these nodes in all the searchers, so we'll just go to
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all_unique_searcher.step()
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# Stop any search tips that are already known as ancestors of the
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stopped_common = common_searcher.stop_searching_any(
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common_searcher.find_seen_ancestors(ancestor_all_unique))
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for searcher in unique_tip_searchers:
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total_stopped += len(searcher.stop_searching_any(
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searcher.find_seen_ancestors(ancestor_all_unique)))
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if 'graph' in debug.debug_flags:
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trace.mutter('For %d unique nodes, created %d + 1 unique searchers'
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' (%d stopped search tips, %d common ancestors'
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' (%d stopped common)',
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len(unique_nodes), len(unique_tip_searchers),
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total_stopped, len(ancestor_all_unique),
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return all_unique_searcher, unique_tip_searchers
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def _step_unique_and_common_searchers(self, common_searcher,
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unique_tip_searchers,
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"""Step all the searchers"""
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newly_seen_common = set(common_searcher.step())
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newly_seen_unique = set()
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for searcher in unique_tip_searchers:
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next = set(searcher.step())
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next.update(unique_searcher.find_seen_ancestors(next))
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next.update(common_searcher.find_seen_ancestors(next))
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for alt_searcher in unique_tip_searchers:
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if alt_searcher is searcher:
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next.update(alt_searcher.find_seen_ancestors(next))
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searcher.start_searching(next)
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newly_seen_unique.update(next)
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return newly_seen_common, newly_seen_unique
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def _find_nodes_common_to_all_unique(self, unique_tip_searchers,
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newly_seen_unique, step_all_unique):
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"""Find nodes that are common to all unique_tip_searchers.
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If it is time, step the all_unique_searcher, and add its nodes to the
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common_to_all_unique_nodes = newly_seen_unique.copy()
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for searcher in unique_tip_searchers:
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common_to_all_unique_nodes.intersection_update(searcher.seen)
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common_to_all_unique_nodes.intersection_update(
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all_unique_searcher.seen)
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# Step all-unique less frequently than the other searchers.
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# In the common case, we don't need to spider out far here, so
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# avoid doing extra work.
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tstart = time.clock()
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nodes = all_unique_searcher.step()
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common_to_all_unique_nodes.update(nodes)
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if 'graph' in debug.debug_flags:
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tdelta = time.clock() - tstart
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trace.mutter('all_unique_searcher step() took %.3fs'
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'for %d nodes (%d total), iteration: %s',
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tdelta, len(nodes), len(all_unique_searcher.seen),
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all_unique_searcher._iterations)
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return common_to_all_unique_nodes
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def _collapse_unique_searchers(self, unique_tip_searchers,
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common_to_all_unique_nodes):
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"""Combine searchers that are searching the same tips.
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When two searchers are searching the same tips, we can stop one of the
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searchers. We also know that the maximal set of common ancestors is the
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intersection of the two original searchers.
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:return: A list of searchers that are searching unique nodes.
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# Filter out searchers that don't actually search different
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# nodes. We already have the ancestry intersection for them
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unique_search_tips = {}
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for searcher in unique_tip_searchers:
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stopped = searcher.stop_searching_any(common_to_all_unique_nodes)
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will_search_set = frozenset(searcher._next_query)
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if not will_search_set:
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if 'graph' in debug.debug_flags:
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trace.mutter('Unique searcher %s was stopped.'
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' (%s iterations) %d nodes stopped',
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searcher._iterations,
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elif will_search_set not in unique_search_tips:
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# This searcher is searching a unique set of nodes, let it
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unique_search_tips[will_search_set] = [searcher]
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unique_search_tips[will_search_set].append(searcher)
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# TODO: it might be possible to collapse searchers faster when they
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# only have *some* search tips in common.
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next_unique_searchers = []
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for searchers in unique_search_tips.itervalues():
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if len(searchers) == 1:
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# Searching unique tips, go for it
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next_unique_searchers.append(searchers[0])
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# These searchers have started searching the same tips, we
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# don't need them to cover the same ground. The
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# intersection of their ancestry won't change, so create a
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# new searcher, combining their histories.
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next_searcher = searchers[0]
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for searcher in searchers[1:]:
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next_searcher.seen.intersection_update(searcher.seen)
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if 'graph' in debug.debug_flags:
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trace.mutter('Combining %d searchers into a single'
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' searcher searching %d nodes with'
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len(next_searcher._next_query),
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len(next_searcher.seen))
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next_unique_searchers.append(next_searcher)
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return next_unique_searchers
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def _refine_unique_nodes(self, unique_searcher, all_unique_searcher,
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unique_tip_searchers, common_searcher):
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"""Steps 5-8 of find_unique_ancestors.
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This function returns when common_searcher has stopped searching for
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# We step the ancestor_all_unique searcher only every
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# STEP_UNIQUE_SEARCHER_EVERY steps.
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step_all_unique_counter = 0
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# While we still have common nodes to search
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while common_searcher._next_query:
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newly_seen_unique) = self._step_unique_and_common_searchers(
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common_searcher, unique_tip_searchers, unique_searcher)
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# These nodes are common ancestors of all unique nodes
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common_to_all_unique_nodes = self._find_nodes_common_to_all_unique(
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unique_tip_searchers, all_unique_searcher, newly_seen_unique,
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step_all_unique_counter==0)
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step_all_unique_counter = ((step_all_unique_counter + 1)
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% STEP_UNIQUE_SEARCHER_EVERY)
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if newly_seen_common:
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# If a 'common' node is an ancestor of all unique searchers, we
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# can stop searching it.
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common_searcher.stop_searching_any(
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all_unique_searcher.seen.intersection(newly_seen_common))
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if common_to_all_unique_nodes:
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common_to_all_unique_nodes.update(
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common_searcher.find_seen_ancestors(
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common_to_all_unique_nodes))
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# The all_unique searcher can start searching the common nodes
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# but everyone else can stop.
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# This is the sort of thing where we would like to not have it
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# start_searching all of the nodes, but only mark all of them
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# as seen, and have it search only the actual tips. Otherwise
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# it is another get_parent_map() traversal for it to figure out
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# what we already should know.
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all_unique_searcher.start_searching(common_to_all_unique_nodes)
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common_searcher.stop_searching_any(common_to_all_unique_nodes)
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next_unique_searchers = self._collapse_unique_searchers(
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unique_tip_searchers, common_to_all_unique_nodes)
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if len(unique_tip_searchers) != len(next_unique_searchers):
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if 'graph' in debug.debug_flags:
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trace.mutter('Collapsed %d unique searchers => %d'
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len(unique_tip_searchers),
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len(next_unique_searchers),
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all_unique_searcher._iterations)
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unique_tip_searchers = next_unique_searchers
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def get_parent_map(self, revisions):
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"""Get a map of key:parent_list for revisions.
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This implementation delegates to get_parents, for old parent_providers
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that do not supply get_parent_map.
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for rev, parents in self.get_parents(revisions):
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if parents is not None:
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result[rev] = parents
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def _make_breadth_first_searcher(self, revisions):
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return _BreadthFirstSearcher(revisions, self)
655
def _find_border_ancestors(self, revisions):
656
"""Find common ancestors with at least one uncommon descendant.
658
Border ancestors are identified using a breadth-first
659
search starting at the bottom of the graph. Searches are stopped
660
whenever a node or one of its descendants is determined to be common.
662
This will scale with the number of uncommon ancestors.
664
As well as the border ancestors, a set of seen common ancestors and a
665
list of sets of seen ancestors for each input revision is returned.
666
This allows calculation of graph difference from the results of this
669
if None in revisions:
670
raise errors.InvalidRevisionId(None, self)
671
common_ancestors = set()
672
searchers = [self._make_breadth_first_searcher([r])
674
active_searchers = searchers[:]
675
border_ancestors = set()
679
for searcher in searchers:
680
new_ancestors = searcher.step()
682
newly_seen.update(new_ancestors)
684
for revision in newly_seen:
685
if revision in common_ancestors:
686
# Not a border ancestor because it was seen as common
688
new_common.add(revision)
690
for searcher in searchers:
691
if revision not in searcher.seen:
694
# This is a border because it is a first common that we see
695
# after walking for a while.
696
border_ancestors.add(revision)
697
new_common.add(revision)
699
for searcher in searchers:
700
new_common.update(searcher.find_seen_ancestors(new_common))
701
for searcher in searchers:
702
searcher.start_searching(new_common)
703
common_ancestors.update(new_common)
705
# Figure out what the searchers will be searching next, and if
706
# there is only 1 set being searched, then we are done searching,
707
# since all searchers would have to be searching the same data,
708
# thus it *must* be in common.
709
unique_search_sets = set()
710
for searcher in searchers:
711
will_search_set = frozenset(searcher._next_query)
712
if will_search_set not in unique_search_sets:
713
# This searcher is searching a unique set of nodes, let it
714
unique_search_sets.add(will_search_set)
716
if len(unique_search_sets) == 1:
717
nodes = unique_search_sets.pop()
718
uncommon_nodes = nodes.difference(common_ancestors)
720
raise AssertionError("Somehow we ended up converging"
721
" without actually marking them as"
724
"\nuncommon_nodes: %s"
725
% (revisions, uncommon_nodes))
727
return border_ancestors, common_ancestors, searchers
729
def heads(self, keys):
730
"""Return the heads from amongst keys.
732
This is done by searching the ancestries of each key. Any key that is
733
reachable from another key is not returned; all the others are.
735
This operation scales with the relative depth between any two keys. If
736
any two keys are completely disconnected all ancestry of both sides
739
:param keys: An iterable of keys.
740
:return: A set of the heads. Note that as a set there is no ordering
741
information. Callers will need to filter their input to create
742
order if they need it.
744
candidate_heads = set(keys)
745
if revision.NULL_REVISION in candidate_heads:
746
# NULL_REVISION is only a head if it is the only entry
747
candidate_heads.remove(revision.NULL_REVISION)
748
if not candidate_heads:
749
return set([revision.NULL_REVISION])
750
if len(candidate_heads) < 2:
751
return candidate_heads
752
searchers = dict((c, self._make_breadth_first_searcher([c]))
753
for c in candidate_heads)
754
active_searchers = dict(searchers)
755
# skip over the actual candidate for each searcher
756
for searcher in active_searchers.itervalues():
758
# The common walker finds nodes that are common to two or more of the
759
# input keys, so that we don't access all history when a currently
760
# uncommon search point actually meets up with something behind a
761
# common search point. Common search points do not keep searches
762
# active; they just allow us to make searches inactive without
763
# accessing all history.
764
common_walker = self._make_breadth_first_searcher([])
765
while len(active_searchers) > 0:
770
except StopIteration:
771
# No common points being searched at this time.
773
for candidate in active_searchers.keys():
775
searcher = active_searchers[candidate]
777
# rare case: we deleted candidate in a previous iteration
778
# through this for loop, because it was determined to be
779
# a descendant of another candidate.
782
ancestors.update(searcher.next())
783
except StopIteration:
784
del active_searchers[candidate]
786
# process found nodes
788
for ancestor in ancestors:
789
if ancestor in candidate_heads:
790
candidate_heads.remove(ancestor)
791
del searchers[ancestor]
792
if ancestor in active_searchers:
793
del active_searchers[ancestor]
794
# it may meet up with a known common node
795
if ancestor in common_walker.seen:
796
# some searcher has encountered our known common nodes:
798
ancestor_set = set([ancestor])
799
for searcher in searchers.itervalues():
800
searcher.stop_searching_any(ancestor_set)
802
# or it may have been just reached by all the searchers:
803
for searcher in searchers.itervalues():
804
if ancestor not in searcher.seen:
807
# The final active searcher has just reached this node,
808
# making it be known as a descendant of all candidates,
809
# so we can stop searching it, and any seen ancestors
810
new_common.add(ancestor)
811
for searcher in searchers.itervalues():
813
searcher.find_seen_ancestors([ancestor])
814
searcher.stop_searching_any(seen_ancestors)
815
common_walker.start_searching(new_common)
816
return candidate_heads
818
def find_merge_order(self, tip_revision_id, lca_revision_ids):
819
"""Find the order that each revision was merged into tip.
821
This basically just walks backwards with a stack, and walks left-first
822
until it finds a node to stop.
824
if len(lca_revision_ids) == 1:
825
return list(lca_revision_ids)
826
looking_for = set(lca_revision_ids)
827
# TODO: Is there a way we could do this "faster" by batching up the
828
# get_parent_map requests?
829
# TODO: Should we also be culling the ancestry search right away? We
830
# could add looking_for to the "stop" list, and walk their
831
# ancestry in batched mode. The flip side is it might mean we walk a
832
# lot of "stop" nodes, rather than only the minimum.
833
# Then again, without it we may trace back into ancestry we could have
835
stack = [tip_revision_id]
838
while stack and looking_for:
841
if next in looking_for:
843
looking_for.remove(next)
844
if len(looking_for) == 1:
845
found.append(looking_for.pop())
848
parent_ids = self.get_parent_map([next]).get(next, None)
849
if not parent_ids: # Ghost, nothing to search here
851
for parent_id in reversed(parent_ids):
852
# TODO: (performance) We see the parent at this point, but we
853
# wait to mark it until later to make sure we get left
854
# parents before right parents. However, instead of
855
# waiting until we have traversed enough parents, we
856
# could instead note that we've found it, and once all
857
# parents are in the stack, just reverse iterate the
859
if parent_id not in stop:
860
# this will need to be searched
861
stack.append(parent_id)
865
def find_unique_lca(self, left_revision, right_revision,
867
"""Find a unique LCA.
869
Find lowest common ancestors. If there is no unique common
870
ancestor, find the lowest common ancestors of those ancestors.
872
Iteration stops when a unique lowest common ancestor is found.
873
The graph origin is necessarily a unique lowest common ancestor.
875
Note that None is not an acceptable substitute for NULL_REVISION.
876
in the input for this method.
878
:param count_steps: If True, the return value will be a tuple of
879
(unique_lca, steps) where steps is the number of times that
880
find_lca was run. If False, only unique_lca is returned.
882
revisions = [left_revision, right_revision]
886
lca = self.find_lca(*revisions)
894
raise errors.NoCommonAncestor(left_revision, right_revision)
897
def iter_ancestry(self, revision_ids):
898
"""Iterate the ancestry of this revision.
900
:param revision_ids: Nodes to start the search
901
:return: Yield tuples mapping a revision_id to its parents for the
902
ancestry of revision_id.
903
Ghosts will be returned with None as their parents, and nodes
904
with no parents will have NULL_REVISION as their only parent. (As
905
defined by get_parent_map.)
906
There will also be a node for (NULL_REVISION, ())
908
pending = set(revision_ids)
911
processed.update(pending)
912
next_map = self.get_parent_map(pending)
914
for item in next_map.iteritems():
916
next_pending.update(p for p in item[1] if p not in processed)
917
ghosts = pending.difference(next_map)
920
pending = next_pending
922
def iter_topo_order(self, revisions):
923
"""Iterate through the input revisions in topological order.
925
This sorting only ensures that parents come before their children.
926
An ancestor may sort after a descendant if the relationship is not
927
visible in the supplied list of revisions.
929
from bzrlib import tsort
930
sorter = tsort.TopoSorter(self.get_parent_map(revisions))
931
return sorter.iter_topo_order()
933
def is_ancestor(self, candidate_ancestor, candidate_descendant):
934
"""Determine whether a revision is an ancestor of another.
936
We answer this using heads() as heads() has the logic to perform the
937
smallest number of parent lookups to determine the ancestral
938
relationship between N revisions.
940
return set([candidate_descendant]) == self.heads(
941
[candidate_ancestor, candidate_descendant])
943
def is_between(self, revid, lower_bound_revid, upper_bound_revid):
944
"""Determine whether a revision is between two others.
946
returns true if and only if:
947
lower_bound_revid <= revid <= upper_bound_revid
949
return ((upper_bound_revid is None or
950
self.is_ancestor(revid, upper_bound_revid)) and
951
(lower_bound_revid is None or
952
self.is_ancestor(lower_bound_revid, revid)))
954
def _search_for_extra_common(self, common, searchers):
955
"""Make sure that unique nodes are genuinely unique.
957
After _find_border_ancestors, all nodes marked "common" are indeed
958
common. Some of the nodes considered unique are not, due to history
959
shortcuts stopping the searches early.
961
We know that we have searched enough when all common search tips are
962
descended from all unique (uncommon) nodes because we know that a node
963
cannot be an ancestor of its own ancestor.
965
:param common: A set of common nodes
966
:param searchers: The searchers returned from _find_border_ancestors
970
# A) The passed in searchers should all be on the same tips, thus
971
# they should be considered the "common" searchers.
972
# B) We find the difference between the searchers, these are the
973
# "unique" nodes for each side.
974
# C) We do a quick culling so that we only start searching from the
975
# more interesting unique nodes. (A unique ancestor is more
976
# interesting than any of its children.)
977
# D) We start searching for ancestors common to all unique nodes.
978
# E) We have the common searchers stop searching any ancestors of
980
# F) When there are no more common search tips, we stop
982
# TODO: We need a way to remove unique_searchers when they overlap with
983
# other unique searchers.
984
if len(searchers) != 2:
985
raise NotImplementedError(
986
"Algorithm not yet implemented for > 2 searchers")
987
common_searchers = searchers
988
left_searcher = searchers[0]
989
right_searcher = searchers[1]
990
unique = left_searcher.seen.symmetric_difference(right_searcher.seen)
991
if not unique: # No unique nodes, nothing to do
993
total_unique = len(unique)
994
unique = self._remove_simple_descendants(unique,
995
self.get_parent_map(unique))
996
simple_unique = len(unique)
998
unique_searchers = []
999
for revision_id in unique:
1000
if revision_id in left_searcher.seen:
1001
parent_searcher = left_searcher
1003
parent_searcher = right_searcher
1004
revs_to_search = parent_searcher.find_seen_ancestors([revision_id])
1005
if not revs_to_search: # XXX: This shouldn't be possible
1006
revs_to_search = [revision_id]
1007
searcher = self._make_breadth_first_searcher(revs_to_search)
1008
# We don't care about the starting nodes.
1010
unique_searchers.append(searcher)
1012
# possible todo: aggregate the common searchers into a single common
1013
# searcher, just make sure that we include the nodes into the .seen
1014
# properties of the original searchers
1016
ancestor_all_unique = None
1017
for searcher in unique_searchers:
1018
if ancestor_all_unique is None:
1019
ancestor_all_unique = set(searcher.seen)
1021
ancestor_all_unique = ancestor_all_unique.intersection(
1024
trace.mutter('Started %s unique searchers for %s unique revisions',
1025
simple_unique, total_unique)
1027
while True: # If we have no more nodes we have nothing to do
1028
newly_seen_common = set()
1029
for searcher in common_searchers:
1030
newly_seen_common.update(searcher.step())
1031
newly_seen_unique = set()
1032
for searcher in unique_searchers:
1033
newly_seen_unique.update(searcher.step())
1034
new_common_unique = set()
1035
for revision in newly_seen_unique:
1036
for searcher in unique_searchers:
1037
if revision not in searcher.seen:
1040
# This is a border because it is a first common that we see
1041
# after walking for a while.
1042
new_common_unique.add(revision)
1043
if newly_seen_common:
1044
# These are nodes descended from one of the 'common' searchers.
1045
# Make sure all searchers are on the same page
1046
for searcher in common_searchers:
1047
newly_seen_common.update(
1048
searcher.find_seen_ancestors(newly_seen_common))
1049
# We start searching the whole ancestry. It is a bit wasteful,
1050
# though. We really just want to mark all of these nodes as
1051
# 'seen' and then start just the tips. However, it requires a
1052
# get_parent_map() call to figure out the tips anyway, and all
1053
# redundant requests should be fairly fast.
1054
for searcher in common_searchers:
1055
searcher.start_searching(newly_seen_common)
1057
# If a 'common' node is an ancestor of all unique searchers, we
1058
# can stop searching it.
1059
stop_searching_common = ancestor_all_unique.intersection(
1061
if stop_searching_common:
1062
for searcher in common_searchers:
1063
searcher.stop_searching_any(stop_searching_common)
1064
if new_common_unique:
1065
# We found some ancestors that are common
1066
for searcher in unique_searchers:
1067
new_common_unique.update(
1068
searcher.find_seen_ancestors(new_common_unique))
1069
# Since these are common, we can grab another set of ancestors
1071
for searcher in common_searchers:
1072
new_common_unique.update(
1073
searcher.find_seen_ancestors(new_common_unique))
1075
# We can tell all of the unique searchers to start at these
1076
# nodes, and tell all of the common searchers to *stop*
1077
# searching these nodes
1078
for searcher in unique_searchers:
1079
searcher.start_searching(new_common_unique)
1080
for searcher in common_searchers:
1081
searcher.stop_searching_any(new_common_unique)
1082
ancestor_all_unique.update(new_common_unique)
1084
# Filter out searchers that don't actually search different
1085
# nodes. We already have the ancestry intersection for them
1086
next_unique_searchers = []
1087
unique_search_sets = set()
1088
for searcher in unique_searchers:
1089
will_search_set = frozenset(searcher._next_query)
1090
if will_search_set not in unique_search_sets:
1091
# This searcher is searching a unique set of nodes, let it
1092
unique_search_sets.add(will_search_set)
1093
next_unique_searchers.append(searcher)
1094
unique_searchers = next_unique_searchers
1095
for searcher in common_searchers:
1096
if searcher._next_query:
1099
# All common searcher have stopped searching
1102
def _remove_simple_descendants(self, revisions, parent_map):
1103
"""remove revisions which are children of other ones in the set
1105
This doesn't do any graph searching, it just checks the immediate
1106
parent_map to find if there are any children which can be removed.
1108
:param revisions: A set of revision_ids
1109
:return: A set of revision_ids with the children removed
1111
simple_ancestors = revisions.copy()
1112
# TODO: jam 20071214 we *could* restrict it to searching only the
1113
# parent_map of revisions already present in 'revisions', but
1114
# considering the general use case, I think this is actually
1117
# This is the same as the following loop. I don't know that it is any
1119
## simple_ancestors.difference_update(r for r, p_ids in parent_map.iteritems()
1120
## if p_ids is not None and revisions.intersection(p_ids))
1121
## return simple_ancestors
1123
# Yet Another Way, invert the parent map (which can be cached)
1125
## for revision_id, parent_ids in parent_map.iteritems():
1126
## for p_id in parent_ids:
1127
## descendants.setdefault(p_id, []).append(revision_id)
1128
## for revision in revisions.intersection(descendants):
1129
## simple_ancestors.difference_update(descendants[revision])
1130
## return simple_ancestors
1131
for revision, parent_ids in parent_map.iteritems():
1132
if parent_ids is None:
1134
for parent_id in parent_ids:
1135
if parent_id in revisions:
1136
# This node has a parent present in the set, so we can
1138
simple_ancestors.discard(revision)
1140
return simple_ancestors
1143
class HeadsCache(object):
1144
"""A cache of results for graph heads calls."""
1146
def __init__(self, graph):
1150
def heads(self, keys):
1151
"""Return the heads of keys.
1153
This matches the API of Graph.heads(), specifically the return value is
1154
a set which can be mutated, and ordering of the input is not preserved
1157
:see also: Graph.heads.
1158
:param keys: The keys to calculate heads for.
1159
:return: A set containing the heads, which may be mutated without
1160
affecting future lookups.
1162
keys = frozenset(keys)
1164
return set(self._heads[keys])
1166
heads = self.graph.heads(keys)
1167
self._heads[keys] = heads
1171
class FrozenHeadsCache(object):
1172
"""Cache heads() calls, assuming the caller won't modify them."""
1174
def __init__(self, graph):
1178
def heads(self, keys):
1179
"""Return the heads of keys.
1181
Similar to Graph.heads(). The main difference is that the return value
1182
is a frozen set which cannot be mutated.
1184
:see also: Graph.heads.
1185
:param keys: The keys to calculate heads for.
1186
:return: A frozenset containing the heads.
1188
keys = frozenset(keys)
1190
return self._heads[keys]
1192
heads = frozenset(self.graph.heads(keys))
1193
self._heads[keys] = heads
1196
def cache(self, keys, heads):
1197
"""Store a known value."""
1198
self._heads[frozenset(keys)] = frozenset(heads)
1201
class _BreadthFirstSearcher(object):
1202
"""Parallel search breadth-first the ancestry of revisions.
1204
This class implements the iterator protocol, but additionally
1205
1. provides a set of seen ancestors, and
1206
2. allows some ancestries to be unsearched, via stop_searching_any
1209
def __init__(self, revisions, parents_provider):
1210
self._iterations = 0
1211
self._next_query = set(revisions)
1213
self._started_keys = set(self._next_query)
1214
self._stopped_keys = set()
1215
self._parents_provider = parents_provider
1216
self._returning = 'next_with_ghosts'
1217
self._current_present = set()
1218
self._current_ghosts = set()
1219
self._current_parents = {}
1222
if self._iterations:
1223
prefix = "searching"
1226
search = '%s=%r' % (prefix, list(self._next_query))
1227
return ('_BreadthFirstSearcher(iterations=%d, %s,'
1228
' seen=%r)' % (self._iterations, search, list(self.seen)))
1230
def get_result(self):
1231
"""Get a SearchResult for the current state of this searcher.
1233
:return: A SearchResult for this search so far. The SearchResult is
1234
static - the search can be advanced and the search result will not
1235
be invalidated or altered.
1237
if self._returning == 'next':
1238
# We have to know the current nodes children to be able to list the
1239
# exclude keys for them. However, while we could have a second
1240
# look-ahead result buffer and shuffle things around, this method
1241
# is typically only called once per search - when memoising the
1242
# results of the search.
1243
found, ghosts, next, parents = self._do_query(self._next_query)
1244
# pretend we didn't query: perhaps we should tweak _do_query to be
1245
# entirely stateless?
1246
self.seen.difference_update(next)
1247
next_query = next.union(ghosts)
1249
next_query = self._next_query
1250
excludes = self._stopped_keys.union(next_query)
1251
included_keys = self.seen.difference(excludes)
1252
return SearchResult(self._started_keys, excludes, len(included_keys),
1258
except StopIteration:
1262
"""Return the next ancestors of this revision.
1264
Ancestors are returned in the order they are seen in a breadth-first
1265
traversal. No ancestor will be returned more than once. Ancestors are
1266
returned before their parentage is queried, so ghosts and missing
1267
revisions (including the start revisions) are included in the result.
1268
This can save a round trip in LCA style calculation by allowing
1269
convergence to be detected without reading the data for the revision
1270
the convergence occurs on.
1272
:return: A set of revision_ids.
1274
if self._returning != 'next':
1275
# switch to returning the query, not the results.
1276
self._returning = 'next'
1277
self._iterations += 1
1280
if len(self._next_query) == 0:
1281
raise StopIteration()
1282
# We have seen what we're querying at this point as we are returning
1283
# the query, not the results.
1284
self.seen.update(self._next_query)
1285
return self._next_query
1287
def next_with_ghosts(self):
1288
"""Return the next found ancestors, with ghosts split out.
1290
Ancestors are returned in the order they are seen in a breadth-first
1291
traversal. No ancestor will be returned more than once. Ancestors are
1292
returned only after asking for their parents, which allows us to detect
1293
which revisions are ghosts and which are not.
1295
:return: A tuple with (present ancestors, ghost ancestors) sets.
1297
if self._returning != 'next_with_ghosts':
1298
# switch to returning the results, not the current query.
1299
self._returning = 'next_with_ghosts'
1301
if len(self._next_query) == 0:
1302
raise StopIteration()
1304
return self._current_present, self._current_ghosts
1307
"""Advance the search.
1309
Updates self.seen, self._next_query, self._current_present,
1310
self._current_ghosts, self._current_parents and self._iterations.
1312
self._iterations += 1
1313
found, ghosts, next, parents = self._do_query(self._next_query)
1314
self._current_present = found
1315
self._current_ghosts = ghosts
1316
self._next_query = next
1317
self._current_parents = parents
1318
# ghosts are implicit stop points, otherwise the search cannot be
1319
# repeated when ghosts are filled.
1320
self._stopped_keys.update(ghosts)
1322
def _do_query(self, revisions):
1323
"""Query for revisions.
1325
Adds revisions to the seen set.
1327
:param revisions: Revisions to query.
1328
:return: A tuple: (set(found_revisions), set(ghost_revisions),
1329
set(parents_of_found_revisions), dict(found_revisions:parents)).
1331
found_revisions = set()
1332
parents_of_found = set()
1333
# revisions may contain nodes that point to other nodes in revisions:
1334
# we want to filter them out.
1335
self.seen.update(revisions)
1336
parent_map = self._parents_provider.get_parent_map(revisions)
1337
found_revisions.update(parent_map)
1338
for rev_id, parents in parent_map.iteritems():
1341
new_found_parents = [p for p in parents if p not in self.seen]
1342
if new_found_parents:
1343
# Calling set.update() with an empty generator is actually
1345
parents_of_found.update(new_found_parents)
1346
ghost_revisions = revisions - found_revisions
1347
return found_revisions, ghost_revisions, parents_of_found, parent_map
1352
def find_seen_ancestors(self, revisions):
1353
"""Find ancestors of these revisions that have already been seen.
1355
This function generally makes the assumption that querying for the
1356
parents of a node that has already been queried is reasonably cheap.
1357
(eg, not a round trip to a remote host).
1359
# TODO: Often we might ask one searcher for its seen ancestors, and
1360
# then ask another searcher the same question. This can result in
1361
# searching the same revisions repeatedly if the two searchers
1362
# have a lot of overlap.
1363
all_seen = self.seen
1364
pending = set(revisions).intersection(all_seen)
1365
seen_ancestors = set(pending)
1367
if self._returning == 'next':
1368
# self.seen contains what nodes have been returned, not what nodes
1369
# have been queried. We don't want to probe for nodes that haven't
1370
# been searched yet.
1371
not_searched_yet = self._next_query
1373
not_searched_yet = ()
1374
pending.difference_update(not_searched_yet)
1375
get_parent_map = self._parents_provider.get_parent_map
1377
parent_map = get_parent_map(pending)
1379
# We don't care if it is a ghost, since it can't be seen if it is
1381
for parent_ids in parent_map.itervalues():
1382
all_parents.extend(parent_ids)
1383
next_pending = all_seen.intersection(all_parents).difference(seen_ancestors)
1384
seen_ancestors.update(next_pending)
1385
next_pending.difference_update(not_searched_yet)
1386
pending = next_pending
1388
return seen_ancestors
1390
def stop_searching_any(self, revisions):
1392
Remove any of the specified revisions from the search list.
1394
None of the specified revisions are required to be present in the
1397
It is okay to call stop_searching_any() for revisions which were seen
1398
in previous iterations. It is the callers responsibility to call
1399
find_seen_ancestors() to make sure that current search tips that are
1400
ancestors of those revisions are also stopped. All explicitly stopped
1401
revisions will be excluded from the search result's get_keys(), though.
1403
# TODO: does this help performance?
1406
revisions = frozenset(revisions)
1407
if self._returning == 'next':
1408
stopped = self._next_query.intersection(revisions)
1409
self._next_query = self._next_query.difference(revisions)
1411
stopped_present = self._current_present.intersection(revisions)
1412
stopped = stopped_present.union(
1413
self._current_ghosts.intersection(revisions))
1414
self._current_present.difference_update(stopped)
1415
self._current_ghosts.difference_update(stopped)
1416
# stopping 'x' should stop returning parents of 'x', but
1417
# not if 'y' always references those same parents
1418
stop_rev_references = {}
1419
for rev in stopped_present:
1420
for parent_id in self._current_parents[rev]:
1421
if parent_id not in stop_rev_references:
1422
stop_rev_references[parent_id] = 0
1423
stop_rev_references[parent_id] += 1
1424
# if only the stopped revisions reference it, the ref count will be
1426
for parents in self._current_parents.itervalues():
1427
for parent_id in parents:
1429
stop_rev_references[parent_id] -= 1
1432
stop_parents = set()
1433
for rev_id, refs in stop_rev_references.iteritems():
1435
stop_parents.add(rev_id)
1436
self._next_query.difference_update(stop_parents)
1437
self._stopped_keys.update(stopped)
1438
self._stopped_keys.update(revisions)
1441
def start_searching(self, revisions):
1442
"""Add revisions to the search.
1444
The parents of revisions will be returned from the next call to next()
1445
or next_with_ghosts(). If next_with_ghosts was the most recently used
1446
next* call then the return value is the result of looking up the
1447
ghost/not ghost status of revisions. (A tuple (present, ghosted)).
1449
revisions = frozenset(revisions)
1450
self._started_keys.update(revisions)
1451
new_revisions = revisions.difference(self.seen)
1452
if self._returning == 'next':
1453
self._next_query.update(new_revisions)
1454
self.seen.update(new_revisions)
1456
# perform a query on revisions
1457
revs, ghosts, query, parents = self._do_query(revisions)
1458
self._stopped_keys.update(ghosts)
1459
self._current_present.update(revs)
1460
self._current_ghosts.update(ghosts)
1461
self._next_query.update(query)
1462
self._current_parents.update(parents)
1466
class SearchResult(object):
1467
"""The result of a breadth first search.
1469
A SearchResult provides the ability to reconstruct the search or access a
1470
set of the keys the search found.
1473
def __init__(self, start_keys, exclude_keys, key_count, keys):
1474
"""Create a SearchResult.
1476
:param start_keys: The keys the search started at.
1477
:param exclude_keys: The keys the search excludes.
1478
:param key_count: The total number of keys (from start to but not
1480
:param keys: The keys the search found. Note that in future we may get
1481
a SearchResult from a smart server, in which case the keys list is
1482
not necessarily immediately available.
1484
self._recipe = ('search', start_keys, exclude_keys, key_count)
1485
self._keys = frozenset(keys)
1487
def get_recipe(self):
1488
"""Return a recipe that can be used to replay this search.
1490
The recipe allows reconstruction of the same results at a later date
1491
without knowing all the found keys. The essential elements are a list
1492
of keys to start and to stop at. In order to give reproducible
1493
results when ghosts are encountered by a search they are automatically
1494
added to the exclude list (or else ghost filling may alter the
1497
:return: A tuple ('search', start_keys_set, exclude_keys_set,
1498
revision_count). To recreate the results of this search, create a
1499
breadth first searcher on the same graph starting at start_keys.
1500
Then call next() (or next_with_ghosts()) repeatedly, and on every
1501
result, call stop_searching_any on any keys from the exclude_keys
1502
set. The revision_count value acts as a trivial cross-check - the
1503
found revisions of the new search should have as many elements as
1504
revision_count. If it does not, then additional revisions have been
1505
ghosted since the search was executed the first time and the second
1511
"""Return the keys found in this search.
1513
:return: A set of keys.
1518
"""Return false if the search lists 1 or more revisions."""
1519
return self._recipe[3] == 0
1521
def refine(self, seen, referenced):
1522
"""Create a new search by refining this search.
1524
:param seen: Revisions that have been satisfied.
1525
:param referenced: Revision references observed while satisfying some
1528
start = self._recipe[1]
1529
exclude = self._recipe[2]
1530
count = self._recipe[3]
1531
keys = self.get_keys()
1532
# New heads = referenced + old heads - seen things - exclude
1533
pending_refs = set(referenced)
1534
pending_refs.update(start)
1535
pending_refs.difference_update(seen)
1536
pending_refs.difference_update(exclude)
1537
# New exclude = old exclude + satisfied heads
1538
seen_heads = start.intersection(seen)
1539
exclude.update(seen_heads)
1540
# keys gets seen removed
1542
# length is reduced by len(seen)
1544
return SearchResult(pending_refs, exclude, count, keys)
1547
class PendingAncestryResult(object):
1548
"""A search result that will reconstruct the ancestry for some graph heads.
1550
Unlike SearchResult, this doesn't hold the complete search result in
1551
memory, it just holds a description of how to generate it.
1554
def __init__(self, heads, repo):
1557
:param heads: an iterable of graph heads.
1558
:param repo: a repository to use to generate the ancestry for the given
1561
self.heads = frozenset(heads)
1564
def get_recipe(self):
1565
"""Return a recipe that can be used to replay this search.
1567
The recipe allows reconstruction of the same results at a later date.
1569
:seealso SearchResult.get_recipe:
1571
:return: A tuple ('proxy-search', start_keys_set, set(), -1)
1572
To recreate this result, create a PendingAncestryResult with the
1575
return ('proxy-search', self.heads, set(), -1)
1578
"""See SearchResult.get_keys.
1580
Returns all the keys for the ancestry of the heads, excluding
1583
return self._get_keys(self.repo.get_graph())
1585
def _get_keys(self, graph):
1586
NULL_REVISION = revision.NULL_REVISION
1587
keys = [key for (key, parents) in graph.iter_ancestry(self.heads)
1588
if key != NULL_REVISION and parents is not None]
1592
"""Return false if the search lists 1 or more revisions."""
1593
if revision.NULL_REVISION in self.heads:
1594
return len(self.heads) == 1
1596
return len(self.heads) == 0
1598
def refine(self, seen, referenced):
1599
"""Create a new search by refining this search.
1601
:param seen: Revisions that have been satisfied.
1602
:param referenced: Revision references observed while satisfying some
1605
referenced = self.heads.union(referenced)
1606
return PendingAncestryResult(referenced - seen, self.repo)
1609
def collapse_linear_regions(parent_map):
1610
"""Collapse regions of the graph that are 'linear'.
1616
can be collapsed by removing B and getting::
1620
:param parent_map: A dictionary mapping children to their parents
1621
:return: Another dictionary with 'linear' chains collapsed
1623
# Note: this isn't a strictly minimal collapse. For example:
1631
# Will not have 'D' removed, even though 'E' could fit. Also:
1637
# A and C are both kept because they are edges of the graph. We *could* get
1638
# rid of A if we wanted.
1646
# Will not have any nodes removed, even though you do have an
1647
# 'uninteresting' linear D->B and E->C
1649
for child, parents in parent_map.iteritems():
1650
children.setdefault(child, [])
1652
children.setdefault(p, []).append(child)
1654
orig_children = dict(children)
1656
result = dict(parent_map)
1657
for node in parent_map:
1658
parents = result[node]
1659
if len(parents) == 1:
1660
parent_children = children[parents[0]]
1661
if len(parent_children) != 1:
1662
# This is not the only child
1664
node_children = children[node]
1665
if len(node_children) != 1:
1667
child_parents = result.get(node_children[0], None)
1668
if len(child_parents) != 1:
1669
# This is not its only parent
1671
# The child of this node only points at it, and the parent only has
1672
# this as a child. remove this node, and join the others together
1673
result[node_children[0]] = parents
1674
children[parents[0]] = node_children
1682
class GraphThunkIdsToKeys(object):
1683
"""Forwards calls about 'ids' to be about keys internally."""
1685
def __init__(self, graph):
1688
def topo_sort(self):
1689
return [r for (r,) in self._graph.topo_sort()]
1691
def heads(self, ids):
1692
"""See Graph.heads()"""
1693
as_keys = [(i,) for i in ids]
1694
head_keys = self._graph.heads(as_keys)
1695
return set([h[0] for h in head_keys])
1697
def merge_sort(self, tip_revision):
1698
return self._graph.merge_sort((tip_revision,))
1701
_counters = [0,0,0,0,0,0,0]
1703
from bzrlib._known_graph_pyx import KnownGraph
1704
except ImportError, e:
1705
osutils.failed_to_load_extension(e)
1706
from bzrlib._known_graph_py import KnownGraph
added
removed
bzrlib/graph.py
