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# Copyright (C) 2007 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., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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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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class _StackedParentsProvider(object):
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def __init__(self, parent_providers):
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self._parent_providers = parent_providers
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return "_StackedParentsProvider(%r)" % 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._cache_misses = 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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def disable_cache(self):
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"""Disable and clear the cache."""
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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((k, v) for k, v in self._cache.items()
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def get_parent_map(self, keys):
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"""See _StackedParentsProvider.get_parent_map."""
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# Hack to build up the caching logic.
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ancestry = self._cache
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# Caching is disabled.
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missing_revisions = set(keys)
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missing_revisions = set(key for key in keys if key not in ancestry)
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if missing_revisions:
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parent_map = self._get_parent_map(missing_revisions)
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ancestry.update(parent_map)
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if self._cache_misses:
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# None is never a valid parents list, so it can be used to
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ancestry.update(dict((k, None) for k in missing_revisions
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if k not in parent_map))
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present_keys = [k for k in keys if ancestry.get(k) is not None]
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return dict((k, ancestry[k]) for k in present_keys)
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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_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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@symbol_versioning.deprecated_method(symbol_versioning.one_one)
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def get_parents(self, revisions):
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"""Find revision ids of the parents of a list of revisions
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A list is returned of the same length as the input. Each entry
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is a list of parent ids for the corresponding input revision.
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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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If the revision is not present (i.e. a ghost), None is used in place
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of the list of parents.
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Deprecated in bzr 1.2 - please see get_parent_map.
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parents = self.get_parent_map(revisions)
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return [parents.get(r, None) for r in revisions]
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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)
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def _find_border_ancestors(self, revisions):
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"""Find common ancestors with at least one uncommon descendant.
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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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This will scale with the number of uncommon ancestors.
645
As well as the border ancestors, a set of seen common ancestors and a
646
list of sets of seen ancestors for each input revision is returned.
647
This allows calculation of graph difference from the results of this
650
if None in revisions:
651
raise errors.InvalidRevisionId(None, self)
652
common_ancestors = set()
653
searchers = [self._make_breadth_first_searcher([r])
655
active_searchers = searchers[:]
656
border_ancestors = set()
660
for searcher in searchers:
661
new_ancestors = searcher.step()
663
newly_seen.update(new_ancestors)
665
for revision in newly_seen:
666
if revision in common_ancestors:
667
# Not a border ancestor because it was seen as common
669
new_common.add(revision)
671
for searcher in searchers:
672
if revision not in searcher.seen:
675
# This is a border because it is a first common that we see
676
# after walking for a while.
677
border_ancestors.add(revision)
678
new_common.add(revision)
680
for searcher in searchers:
681
new_common.update(searcher.find_seen_ancestors(new_common))
682
for searcher in searchers:
683
searcher.start_searching(new_common)
684
common_ancestors.update(new_common)
686
# Figure out what the searchers will be searching next, and if
687
# there is only 1 set being searched, then we are done searching,
688
# since all searchers would have to be searching the same data,
689
# thus it *must* be in common.
690
unique_search_sets = set()
691
for searcher in searchers:
692
will_search_set = frozenset(searcher._next_query)
693
if will_search_set not in unique_search_sets:
694
# This searcher is searching a unique set of nodes, let it
695
unique_search_sets.add(will_search_set)
697
if len(unique_search_sets) == 1:
698
nodes = unique_search_sets.pop()
699
uncommon_nodes = nodes.difference(common_ancestors)
701
raise AssertionError("Somehow we ended up converging"
702
" without actually marking them as"
705
"\nuncommon_nodes: %s"
706
% (revisions, uncommon_nodes))
708
return border_ancestors, common_ancestors, searchers
710
def heads(self, keys):
711
"""Return the heads from amongst keys.
713
This is done by searching the ancestries of each key. Any key that is
714
reachable from another key is not returned; all the others are.
716
This operation scales with the relative depth between any two keys. If
717
any two keys are completely disconnected all ancestry of both sides
720
:param keys: An iterable of keys.
721
:return: A set of the heads. Note that as a set there is no ordering
722
information. Callers will need to filter their input to create
723
order if they need it.
725
candidate_heads = set(keys)
726
if revision.NULL_REVISION in candidate_heads:
727
# NULL_REVISION is only a head if it is the only entry
728
candidate_heads.remove(revision.NULL_REVISION)
729
if not candidate_heads:
730
return set([revision.NULL_REVISION])
731
if len(candidate_heads) < 2:
732
return candidate_heads
733
searchers = dict((c, self._make_breadth_first_searcher([c]))
734
for c in candidate_heads)
735
active_searchers = dict(searchers)
736
# skip over the actual candidate for each searcher
737
for searcher in active_searchers.itervalues():
739
# The common walker finds nodes that are common to two or more of the
740
# input keys, so that we don't access all history when a currently
741
# uncommon search point actually meets up with something behind a
742
# common search point. Common search points do not keep searches
743
# active; they just allow us to make searches inactive without
744
# accessing all history.
745
common_walker = self._make_breadth_first_searcher([])
746
while len(active_searchers) > 0:
751
except StopIteration:
752
# No common points being searched at this time.
754
for candidate in active_searchers.keys():
756
searcher = active_searchers[candidate]
758
# rare case: we deleted candidate in a previous iteration
759
# through this for loop, because it was determined to be
760
# a descendant of another candidate.
763
ancestors.update(searcher.next())
764
except StopIteration:
765
del active_searchers[candidate]
767
# process found nodes
769
for ancestor in ancestors:
770
if ancestor in candidate_heads:
771
candidate_heads.remove(ancestor)
772
del searchers[ancestor]
773
if ancestor in active_searchers:
774
del active_searchers[ancestor]
775
# it may meet up with a known common node
776
if ancestor in common_walker.seen:
777
# some searcher has encountered our known common nodes:
779
ancestor_set = set([ancestor])
780
for searcher in searchers.itervalues():
781
searcher.stop_searching_any(ancestor_set)
783
# or it may have been just reached by all the searchers:
784
for searcher in searchers.itervalues():
785
if ancestor not in searcher.seen:
788
# The final active searcher has just reached this node,
789
# making it be known as a descendant of all candidates,
790
# so we can stop searching it, and any seen ancestors
791
new_common.add(ancestor)
792
for searcher in searchers.itervalues():
794
searcher.find_seen_ancestors([ancestor])
795
searcher.stop_searching_any(seen_ancestors)
796
common_walker.start_searching(new_common)
797
return candidate_heads
799
def find_merge_order(self, tip_revision_id, lca_revision_ids):
800
"""Find the order that each revision was merged into tip.
802
This basically just walks backwards with a stack, and walks left-first
803
until it finds a node to stop.
805
if len(lca_revision_ids) == 1:
806
return list(lca_revision_ids)
807
looking_for = set(lca_revision_ids)
808
# TODO: Is there a way we could do this "faster" by batching up the
809
# get_parent_map requests?
810
# TODO: Should we also be culling the ancestry search right away? We
811
# could add looking_for to the "stop" list, and walk their
812
# ancestry in batched mode. The flip side is it might mean we walk a
813
# lot of "stop" nodes, rather than only the minimum.
814
# Then again, without it we may trace back into ancestry we could have
816
stack = [tip_revision_id]
819
while stack and looking_for:
822
if next in looking_for:
824
looking_for.remove(next)
825
if len(looking_for) == 1:
826
found.append(looking_for.pop())
829
parent_ids = self.get_parent_map([next]).get(next, None)
830
if not parent_ids: # Ghost, nothing to search here
832
for parent_id in reversed(parent_ids):
833
# TODO: (performance) We see the parent at this point, but we
834
# wait to mark it until later to make sure we get left
835
# parents before right parents. However, instead of
836
# waiting until we have traversed enough parents, we
837
# could instead note that we've found it, and once all
838
# parents are in the stack, just reverse iterate the
840
if parent_id not in stop:
841
# this will need to be searched
842
stack.append(parent_id)
846
def find_unique_lca(self, left_revision, right_revision,
848
"""Find a unique LCA.
850
Find lowest common ancestors. If there is no unique common
851
ancestor, find the lowest common ancestors of those ancestors.
853
Iteration stops when a unique lowest common ancestor is found.
854
The graph origin is necessarily a unique lowest common ancestor.
856
Note that None is not an acceptable substitute for NULL_REVISION.
857
in the input for this method.
859
:param count_steps: If True, the return value will be a tuple of
860
(unique_lca, steps) where steps is the number of times that
861
find_lca was run. If False, only unique_lca is returned.
863
revisions = [left_revision, right_revision]
867
lca = self.find_lca(*revisions)
875
raise errors.NoCommonAncestor(left_revision, right_revision)
878
def iter_ancestry(self, revision_ids):
879
"""Iterate the ancestry of this revision.
881
:param revision_ids: Nodes to start the search
882
:return: Yield tuples mapping a revision_id to its parents for the
883
ancestry of revision_id.
884
Ghosts will be returned with None as their parents, and nodes
885
with no parents will have NULL_REVISION as their only parent. (As
886
defined by get_parent_map.)
887
There will also be a node for (NULL_REVISION, ())
889
pending = set(revision_ids)
892
processed.update(pending)
893
next_map = self.get_parent_map(pending)
895
for item in next_map.iteritems():
897
next_pending.update(p for p in item[1] if p not in processed)
898
ghosts = pending.difference(next_map)
901
pending = next_pending
903
def iter_topo_order(self, revisions):
904
"""Iterate through the input revisions in topological order.
906
This sorting only ensures that parents come before their children.
907
An ancestor may sort after a descendant if the relationship is not
908
visible in the supplied list of revisions.
910
sorter = tsort.TopoSorter(self.get_parent_map(revisions))
911
return sorter.iter_topo_order()
913
def is_ancestor(self, candidate_ancestor, candidate_descendant):
914
"""Determine whether a revision is an ancestor of another.
916
We answer this using heads() as heads() has the logic to perform the
917
smallest number of parent lookups to determine the ancestral
918
relationship between N revisions.
920
return set([candidate_descendant]) == self.heads(
921
[candidate_ancestor, candidate_descendant])
923
def _search_for_extra_common(self, common, searchers):
924
"""Make sure that unique nodes are genuinely unique.
926
After _find_border_ancestors, all nodes marked "common" are indeed
927
common. Some of the nodes considered unique are not, due to history
928
shortcuts stopping the searches early.
930
We know that we have searched enough when all common search tips are
931
descended from all unique (uncommon) nodes because we know that a node
932
cannot be an ancestor of its own ancestor.
934
:param common: A set of common nodes
935
:param searchers: The searchers returned from _find_border_ancestors
939
# A) The passed in searchers should all be on the same tips, thus
940
# they should be considered the "common" searchers.
941
# B) We find the difference between the searchers, these are the
942
# "unique" nodes for each side.
943
# C) We do a quick culling so that we only start searching from the
944
# more interesting unique nodes. (A unique ancestor is more
945
# interesting than any of its children.)
946
# D) We start searching for ancestors common to all unique nodes.
947
# E) We have the common searchers stop searching any ancestors of
949
# F) When there are no more common search tips, we stop
951
# TODO: We need a way to remove unique_searchers when they overlap with
952
# other unique searchers.
953
if len(searchers) != 2:
954
raise NotImplementedError(
955
"Algorithm not yet implemented for > 2 searchers")
956
common_searchers = searchers
957
left_searcher = searchers[0]
958
right_searcher = searchers[1]
959
unique = left_searcher.seen.symmetric_difference(right_searcher.seen)
960
if not unique: # No unique nodes, nothing to do
962
total_unique = len(unique)
963
unique = self._remove_simple_descendants(unique,
964
self.get_parent_map(unique))
965
simple_unique = len(unique)
967
unique_searchers = []
968
for revision_id in unique:
969
if revision_id in left_searcher.seen:
970
parent_searcher = left_searcher
972
parent_searcher = right_searcher
973
revs_to_search = parent_searcher.find_seen_ancestors([revision_id])
974
if not revs_to_search: # XXX: This shouldn't be possible
975
revs_to_search = [revision_id]
976
searcher = self._make_breadth_first_searcher(revs_to_search)
977
# We don't care about the starting nodes.
979
unique_searchers.append(searcher)
981
# possible todo: aggregate the common searchers into a single common
982
# searcher, just make sure that we include the nodes into the .seen
983
# properties of the original searchers
985
ancestor_all_unique = None
986
for searcher in unique_searchers:
987
if ancestor_all_unique is None:
988
ancestor_all_unique = set(searcher.seen)
990
ancestor_all_unique = ancestor_all_unique.intersection(
993
trace.mutter('Started %s unique searchers for %s unique revisions',
994
simple_unique, total_unique)
996
while True: # If we have no more nodes we have nothing to do
997
newly_seen_common = set()
998
for searcher in common_searchers:
999
newly_seen_common.update(searcher.step())
1000
newly_seen_unique = set()
1001
for searcher in unique_searchers:
1002
newly_seen_unique.update(searcher.step())
1003
new_common_unique = set()
1004
for revision in newly_seen_unique:
1005
for searcher in unique_searchers:
1006
if revision not in searcher.seen:
1009
# This is a border because it is a first common that we see
1010
# after walking for a while.
1011
new_common_unique.add(revision)
1012
if newly_seen_common:
1013
# These are nodes descended from one of the 'common' searchers.
1014
# Make sure all searchers are on the same page
1015
for searcher in common_searchers:
1016
newly_seen_common.update(
1017
searcher.find_seen_ancestors(newly_seen_common))
1018
# We start searching the whole ancestry. It is a bit wasteful,
1019
# though. We really just want to mark all of these nodes as
1020
# 'seen' and then start just the tips. However, it requires a
1021
# get_parent_map() call to figure out the tips anyway, and all
1022
# redundant requests should be fairly fast.
1023
for searcher in common_searchers:
1024
searcher.start_searching(newly_seen_common)
1026
# If a 'common' node is an ancestor of all unique searchers, we
1027
# can stop searching it.
1028
stop_searching_common = ancestor_all_unique.intersection(
1030
if stop_searching_common:
1031
for searcher in common_searchers:
1032
searcher.stop_searching_any(stop_searching_common)
1033
if new_common_unique:
1034
# We found some ancestors that are common
1035
for searcher in unique_searchers:
1036
new_common_unique.update(
1037
searcher.find_seen_ancestors(new_common_unique))
1038
# Since these are common, we can grab another set of ancestors
1040
for searcher in common_searchers:
1041
new_common_unique.update(
1042
searcher.find_seen_ancestors(new_common_unique))
1044
# We can tell all of the unique searchers to start at these
1045
# nodes, and tell all of the common searchers to *stop*
1046
# searching these nodes
1047
for searcher in unique_searchers:
1048
searcher.start_searching(new_common_unique)
1049
for searcher in common_searchers:
1050
searcher.stop_searching_any(new_common_unique)
1051
ancestor_all_unique.update(new_common_unique)
1053
# Filter out searchers that don't actually search different
1054
# nodes. We already have the ancestry intersection for them
1055
next_unique_searchers = []
1056
unique_search_sets = set()
1057
for searcher in unique_searchers:
1058
will_search_set = frozenset(searcher._next_query)
1059
if will_search_set not in unique_search_sets:
1060
# This searcher is searching a unique set of nodes, let it
1061
unique_search_sets.add(will_search_set)
1062
next_unique_searchers.append(searcher)
1063
unique_searchers = next_unique_searchers
1064
for searcher in common_searchers:
1065
if searcher._next_query:
1068
# All common searcher have stopped searching
1071
def _remove_simple_descendants(self, revisions, parent_map):
1072
"""remove revisions which are children of other ones in the set
1074
This doesn't do any graph searching, it just checks the immediate
1075
parent_map to find if there are any children which can be removed.
1077
:param revisions: A set of revision_ids
1078
:return: A set of revision_ids with the children removed
1080
simple_ancestors = revisions.copy()
1081
# TODO: jam 20071214 we *could* restrict it to searching only the
1082
# parent_map of revisions already present in 'revisions', but
1083
# considering the general use case, I think this is actually
1086
# This is the same as the following loop. I don't know that it is any
1088
## simple_ancestors.difference_update(r for r, p_ids in parent_map.iteritems()
1089
## if p_ids is not None and revisions.intersection(p_ids))
1090
## return simple_ancestors
1092
# Yet Another Way, invert the parent map (which can be cached)
1094
## for revision_id, parent_ids in parent_map.iteritems():
1095
## for p_id in parent_ids:
1096
## descendants.setdefault(p_id, []).append(revision_id)
1097
## for revision in revisions.intersection(descendants):
1098
## simple_ancestors.difference_update(descendants[revision])
1099
## return simple_ancestors
1100
for revision, parent_ids in parent_map.iteritems():
1101
if parent_ids is None:
1103
for parent_id in parent_ids:
1104
if parent_id in revisions:
1105
# This node has a parent present in the set, so we can
1107
simple_ancestors.discard(revision)
1109
return simple_ancestors
1112
class HeadsCache(object):
1113
"""A cache of results for graph heads calls."""
1115
def __init__(self, graph):
1119
def heads(self, keys):
1120
"""Return the heads of keys.
1122
This matches the API of Graph.heads(), specifically the return value is
1123
a set which can be mutated, and ordering of the input is not preserved
1126
:see also: Graph.heads.
1127
:param keys: The keys to calculate heads for.
1128
:return: A set containing the heads, which may be mutated without
1129
affecting future lookups.
1131
keys = frozenset(keys)
1133
return set(self._heads[keys])
1135
heads = self.graph.heads(keys)
1136
self._heads[keys] = heads
1140
class FrozenHeadsCache(object):
1141
"""Cache heads() calls, assuming the caller won't modify them."""
1143
def __init__(self, graph):
1147
def heads(self, keys):
1148
"""Return the heads of keys.
1150
Similar to Graph.heads(). The main difference is that the return value
1151
is a frozen set which cannot be mutated.
1153
:see also: Graph.heads.
1154
:param keys: The keys to calculate heads for.
1155
:return: A frozenset containing the heads.
1157
keys = frozenset(keys)
1159
return self._heads[keys]
1161
heads = frozenset(self.graph.heads(keys))
1162
self._heads[keys] = heads
1165
def cache(self, keys, heads):
1166
"""Store a known value."""
1167
self._heads[frozenset(keys)] = frozenset(heads)
1170
class _BreadthFirstSearcher(object):
1171
"""Parallel search breadth-first the ancestry of revisions.
1173
This class implements the iterator protocol, but additionally
1174
1. provides a set of seen ancestors, and
1175
2. allows some ancestries to be unsearched, via stop_searching_any
1178
def __init__(self, revisions, parents_provider):
1179
self._iterations = 0
1180
self._next_query = set(revisions)
1182
self._started_keys = set(self._next_query)
1183
self._stopped_keys = set()
1184
self._parents_provider = parents_provider
1185
self._returning = 'next_with_ghosts'
1186
self._current_present = set()
1187
self._current_ghosts = set()
1188
self._current_parents = {}
1191
if self._iterations:
1192
prefix = "searching"
1195
search = '%s=%r' % (prefix, list(self._next_query))
1196
return ('_BreadthFirstSearcher(iterations=%d, %s,'
1197
' seen=%r)' % (self._iterations, search, list(self.seen)))
1199
def get_result(self):
1200
"""Get a SearchResult for the current state of this searcher.
1202
:return: A SearchResult for this search so far. The SearchResult is
1203
static - the search can be advanced and the search result will not
1204
be invalidated or altered.
1206
if self._returning == 'next':
1207
# We have to know the current nodes children to be able to list the
1208
# exclude keys for them. However, while we could have a second
1209
# look-ahead result buffer and shuffle things around, this method
1210
# is typically only called once per search - when memoising the
1211
# results of the search.
1212
found, ghosts, next, parents = self._do_query(self._next_query)
1213
# pretend we didn't query: perhaps we should tweak _do_query to be
1214
# entirely stateless?
1215
self.seen.difference_update(next)
1216
next_query = next.union(ghosts)
1218
next_query = self._next_query
1219
excludes = self._stopped_keys.union(next_query)
1220
included_keys = self.seen.difference(excludes)
1221
return SearchResult(self._started_keys, excludes, len(included_keys),
1227
except StopIteration:
1231
"""Return the next ancestors of this revision.
1233
Ancestors are returned in the order they are seen in a breadth-first
1234
traversal. No ancestor will be returned more than once. Ancestors are
1235
returned before their parentage is queried, so ghosts and missing
1236
revisions (including the start revisions) are included in the result.
1237
This can save a round trip in LCA style calculation by allowing
1238
convergence to be detected without reading the data for the revision
1239
the convergence occurs on.
1241
:return: A set of revision_ids.
1243
if self._returning != 'next':
1244
# switch to returning the query, not the results.
1245
self._returning = 'next'
1246
self._iterations += 1
1249
if len(self._next_query) == 0:
1250
raise StopIteration()
1251
# We have seen what we're querying at this point as we are returning
1252
# the query, not the results.
1253
self.seen.update(self._next_query)
1254
return self._next_query
1256
def next_with_ghosts(self):
1257
"""Return the next found ancestors, with ghosts split out.
1259
Ancestors are returned in the order they are seen in a breadth-first
1260
traversal. No ancestor will be returned more than once. Ancestors are
1261
returned only after asking for their parents, which allows us to detect
1262
which revisions are ghosts and which are not.
1264
:return: A tuple with (present ancestors, ghost ancestors) sets.
1266
if self._returning != 'next_with_ghosts':
1267
# switch to returning the results, not the current query.
1268
self._returning = 'next_with_ghosts'
1270
if len(self._next_query) == 0:
1271
raise StopIteration()
1273
return self._current_present, self._current_ghosts
1276
"""Advance the search.
1278
Updates self.seen, self._next_query, self._current_present,
1279
self._current_ghosts, self._current_parents and self._iterations.
1281
self._iterations += 1
1282
found, ghosts, next, parents = self._do_query(self._next_query)
1283
self._current_present = found
1284
self._current_ghosts = ghosts
1285
self._next_query = next
1286
self._current_parents = parents
1287
# ghosts are implicit stop points, otherwise the search cannot be
1288
# repeated when ghosts are filled.
1289
self._stopped_keys.update(ghosts)
1291
def _do_query(self, revisions):
1292
"""Query for revisions.
1294
Adds revisions to the seen set.
1296
:param revisions: Revisions to query.
1297
:return: A tuple: (set(found_revisions), set(ghost_revisions),
1298
set(parents_of_found_revisions), dict(found_revisions:parents)).
1300
found_revisions = set()
1301
parents_of_found = set()
1302
# revisions may contain nodes that point to other nodes in revisions:
1303
# we want to filter them out.
1304
self.seen.update(revisions)
1305
parent_map = self._parents_provider.get_parent_map(revisions)
1306
found_revisions.update(parent_map)
1307
for rev_id, parents in parent_map.iteritems():
1310
new_found_parents = [p for p in parents if p not in self.seen]
1311
if new_found_parents:
1312
# Calling set.update() with an empty generator is actually
1314
parents_of_found.update(new_found_parents)
1315
ghost_revisions = revisions - found_revisions
1316
return found_revisions, ghost_revisions, parents_of_found, parent_map
1321
def find_seen_ancestors(self, revisions):
1322
"""Find ancestors of these revisions that have already been seen.
1324
This function generally makes the assumption that querying for the
1325
parents of a node that has already been queried is reasonably cheap.
1326
(eg, not a round trip to a remote host).
1328
# TODO: Often we might ask one searcher for its seen ancestors, and
1329
# then ask another searcher the same question. This can result in
1330
# searching the same revisions repeatedly if the two searchers
1331
# have a lot of overlap.
1332
all_seen = self.seen
1333
pending = set(revisions).intersection(all_seen)
1334
seen_ancestors = set(pending)
1336
if self._returning == 'next':
1337
# self.seen contains what nodes have been returned, not what nodes
1338
# have been queried. We don't want to probe for nodes that haven't
1339
# been searched yet.
1340
not_searched_yet = self._next_query
1342
not_searched_yet = ()
1343
pending.difference_update(not_searched_yet)
1344
get_parent_map = self._parents_provider.get_parent_map
1346
parent_map = get_parent_map(pending)
1348
# We don't care if it is a ghost, since it can't be seen if it is
1350
for parent_ids in parent_map.itervalues():
1351
all_parents.extend(parent_ids)
1352
next_pending = all_seen.intersection(all_parents).difference(seen_ancestors)
1353
seen_ancestors.update(next_pending)
1354
next_pending.difference_update(not_searched_yet)
1355
pending = next_pending
1357
return seen_ancestors
1359
def stop_searching_any(self, revisions):
1361
Remove any of the specified revisions from the search list.
1363
None of the specified revisions are required to be present in the
1366
It is okay to call stop_searching_any() for revisions which were seen
1367
in previous iterations. It is the callers responsibility to call
1368
find_seen_ancestors() to make sure that current search tips that are
1369
ancestors of those revisions are also stopped. All explicitly stopped
1370
revisions will be excluded from the search result's get_keys(), though.
1372
# TODO: does this help performance?
1375
revisions = frozenset(revisions)
1376
if self._returning == 'next':
1377
stopped = self._next_query.intersection(revisions)
1378
self._next_query = self._next_query.difference(revisions)
1380
stopped_present = self._current_present.intersection(revisions)
1381
stopped = stopped_present.union(
1382
self._current_ghosts.intersection(revisions))
1383
self._current_present.difference_update(stopped)
1384
self._current_ghosts.difference_update(stopped)
1385
# stopping 'x' should stop returning parents of 'x', but
1386
# not if 'y' always references those same parents
1387
stop_rev_references = {}
1388
for rev in stopped_present:
1389
for parent_id in self._current_parents[rev]:
1390
if parent_id not in stop_rev_references:
1391
stop_rev_references[parent_id] = 0
1392
stop_rev_references[parent_id] += 1
1393
# if only the stopped revisions reference it, the ref count will be
1395
for parents in self._current_parents.itervalues():
1396
for parent_id in parents:
1398
stop_rev_references[parent_id] -= 1
1401
stop_parents = set()
1402
for rev_id, refs in stop_rev_references.iteritems():
1404
stop_parents.add(rev_id)
1405
self._next_query.difference_update(stop_parents)
1406
self._stopped_keys.update(stopped)
1407
self._stopped_keys.update(revisions - set([revision.NULL_REVISION]))
1410
def start_searching(self, revisions):
1411
"""Add revisions to the search.
1413
The parents of revisions will be returned from the next call to next()
1414
or next_with_ghosts(). If next_with_ghosts was the most recently used
1415
next* call then the return value is the result of looking up the
1416
ghost/not ghost status of revisions. (A tuple (present, ghosted)).
1418
revisions = frozenset(revisions)
1419
self._started_keys.update(revisions)
1420
new_revisions = revisions.difference(self.seen)
1421
if self._returning == 'next':
1422
self._next_query.update(new_revisions)
1423
self.seen.update(new_revisions)
1425
# perform a query on revisions
1426
revs, ghosts, query, parents = self._do_query(revisions)
1427
self._stopped_keys.update(ghosts)
1428
self._current_present.update(revs)
1429
self._current_ghosts.update(ghosts)
1430
self._next_query.update(query)
1431
self._current_parents.update(parents)
1435
class SearchResult(object):
1436
"""The result of a breadth first search.
1438
A SearchResult provides the ability to reconstruct the search or access a
1439
set of the keys the search found.
1442
def __init__(self, start_keys, exclude_keys, key_count, keys):
1443
"""Create a SearchResult.
1445
:param start_keys: The keys the search started at.
1446
:param exclude_keys: The keys the search excludes.
1447
:param key_count: The total number of keys (from start to but not
1449
:param keys: The keys the search found. Note that in future we may get
1450
a SearchResult from a smart server, in which case the keys list is
1451
not necessarily immediately available.
1453
self._recipe = (start_keys, exclude_keys, key_count)
1454
self._keys = frozenset(keys)
1456
def get_recipe(self):
1457
"""Return a recipe that can be used to replay this search.
1459
The recipe allows reconstruction of the same results at a later date
1460
without knowing all the found keys. The essential elements are a list
1461
of keys to start and and to stop at. In order to give reproducible
1462
results when ghosts are encountered by a search they are automatically
1463
added to the exclude list (or else ghost filling may alter the
1466
:return: A tuple (start_keys_set, exclude_keys_set, revision_count). To
1467
recreate the results of this search, create a breadth first
1468
searcher on the same graph starting at start_keys. Then call next()
1469
(or next_with_ghosts()) repeatedly, and on every result, call
1470
stop_searching_any on any keys from the exclude_keys set. The
1471
revision_count value acts as a trivial cross-check - the found
1472
revisions of the new search should have as many elements as
1473
revision_count. If it does not, then additional revisions have been
1474
ghosted since the search was executed the first time and the second
1480
"""Return the keys found in this search.
1482
:return: A set of keys.
1487
def collapse_linear_regions(parent_map):
1488
"""Collapse regions of the graph that are 'linear'.
1494
can be collapsed by removing B and getting::
1498
:param parent_map: A dictionary mapping children to their parents
1499
:return: Another dictionary with 'linear' chains collapsed
1501
# Note: this isn't a strictly minimal collapse. For example:
1509
# Will not have 'D' removed, even though 'E' could fit. Also:
1515
# A and C are both kept because they are edges of the graph. We *could* get
1516
# rid of A if we wanted.
1524
# Will not have any nodes removed, even though you do have an
1525
# 'uninteresting' linear D->B and E->C
1527
for child, parents in parent_map.iteritems():
1528
children.setdefault(child, [])
1530
children.setdefault(p, []).append(child)
1532
orig_children = dict(children)
1534
result = dict(parent_map)
1535
for node in parent_map:
1536
parents = result[node]
1537
if len(parents) == 1:
1538
parent_children = children[parents[0]]
1539
if len(parent_children) != 1:
1540
# This is not the only child
1542
node_children = children[node]
1543
if len(node_children) != 1:
1545
child_parents = result.get(node_children[0], None)
1546
if len(child_parents) != 1:
1547
# This is not its only parent
1549
# The child of this node only points at it, and the parent only has
1550
# this as a child. remove this node, and join the others together
1551
result[node_children[0]] = parents
1552
children[parents[0]] = node_children
added
removed
bzrlib/graph.py
