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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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from bzrlib.deprecated_graph import (node_distances, select_farthest)
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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 in a dict.
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This is useful for providers that have an expensive lookup.
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def __init__(self, parent_provider):
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self._real_provider = parent_provider
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# Theoretically we could use an LRUCache here
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return "%s(%r)" % (self.__class__.__name__, self._real_provider)
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def get_parent_map(self, keys):
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"""See _StackedParentsProvider.get_parent_map"""
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# If the _real_provider doesn't have a key, we cache a value of None,
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# which we then later use to realize we cannot provide a value for that
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if value is not None:
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parent_map[key] = value
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new_parents = self._real_provider.get_parent_map(needed)
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cache.update(new_parents)
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parent_map.update(new_parents)
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needed.difference_update(new_parents)
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cache.update(dict.fromkeys(needed, None))
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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, (left, right) = self._find_border_ancestors(
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[left_revision, right_revision])
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return (left.difference(right).difference(common),
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right.difference(left).difference(common))
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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 [parent.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.
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As well as the border ancestors, a set of seen common ancestors and a
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list of sets of seen ancestors for each input revision is returned.
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This allows calculation of graph difference from the results of this
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if None in revisions:
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raise errors.InvalidRevisionId(None, self)
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common_searcher = self._make_breadth_first_searcher([])
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common_ancestors = set()
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searchers = [self._make_breadth_first_searcher([r])
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active_searchers = searchers[:]
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border_ancestors = set()
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def update_common(searcher, revisions):
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w_seen_ancestors = searcher.find_seen_ancestors(
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stopped = searcher.stop_searching_any(w_seen_ancestors)
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common_ancestors.update(w_seen_ancestors)
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common_searcher.start_searching(stopped)
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if len(active_searchers) == 0:
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return border_ancestors, common_ancestors, [s.seen for s in
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new_common = common_searcher.next()
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common_ancestors.update(new_common)
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except StopIteration:
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for searcher in active_searchers:
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for revision in new_common.intersection(searcher.seen):
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update_common(searcher, revision)
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new_active_searchers = []
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for searcher in active_searchers:
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newly_seen.update(searcher.next())
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except StopIteration:
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new_active_searchers.append(searcher)
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active_searchers = new_active_searchers
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for revision in newly_seen:
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if revision in common_ancestors:
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for searcher in searchers:
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update_common(searcher, revision)
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for searcher in searchers:
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if revision not in searcher.seen:
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border_ancestors.add(revision)
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for searcher in searchers:
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update_common(searcher, revision)
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def heads(self, keys):
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"""Return the heads from amongst keys.
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This is done by searching the ancestries of each key. Any key that is
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reachable from another key is not returned; all the others are.
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This operation scales with the relative depth between any two keys. If
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any two keys are completely disconnected all ancestry of both sides
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:param keys: An iterable of keys.
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:return: A set of the heads. Note that as a set there is no ordering
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information. Callers will need to filter their input to create
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order if they need it.
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candidate_heads = set(keys)
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if revision.NULL_REVISION in candidate_heads:
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# NULL_REVISION is only a head if it is the only entry
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candidate_heads.remove(revision.NULL_REVISION)
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if not candidate_heads:
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return set([revision.NULL_REVISION])
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if len(candidate_heads) < 2:
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return candidate_heads
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searchers = dict((c, self._make_breadth_first_searcher([c]))
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for c in candidate_heads)
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active_searchers = dict(searchers)
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# skip over the actual candidate for each searcher
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for searcher in active_searchers.itervalues():
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# The common walker finds nodes that are common to two or more of the
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# input keys, so that we don't access all history when a currently
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# uncommon search point actually meets up with something behind a
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# common search point. Common search points do not keep searches
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# active; they just allow us to make searches inactive without
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# accessing all history.
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common_walker = self._make_breadth_first_searcher([])
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while len(active_searchers) > 0:
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except StopIteration:
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# No common points being searched at this time.
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for candidate in active_searchers.keys():
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searcher = active_searchers[candidate]
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# rare case: we deleted candidate in a previous iteration
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# through this for loop, because it was determined to be
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# a descendant of another candidate.
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ancestors.update(searcher.next())
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except StopIteration:
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del active_searchers[candidate]
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# process found nodes
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for ancestor in ancestors:
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if ancestor in candidate_heads:
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candidate_heads.remove(ancestor)
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del searchers[ancestor]
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if ancestor in active_searchers:
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del active_searchers[ancestor]
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# it may meet up with a known common node
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if ancestor in common_walker.seen:
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# some searcher has encountered our known common nodes:
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ancestor_set = set([ancestor])
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for searcher in searchers.itervalues():
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searcher.stop_searching_any(ancestor_set)
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# or it may have been just reached by all the searchers:
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for searcher in searchers.itervalues():
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if ancestor not in searcher.seen:
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# The final active searcher has just reached this node,
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# making it be known as a descendant of all candidates,
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# so we can stop searching it, and any seen ancestors
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new_common.add(ancestor)
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for searcher in searchers.itervalues():
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searcher.find_seen_ancestors(ancestor)
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searcher.stop_searching_any(seen_ancestors)
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common_walker.start_searching(new_common)
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return candidate_heads
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def find_unique_lca(self, left_revision, right_revision,
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"""Find a unique LCA.
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Find lowest common ancestors. If there is no unique common
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ancestor, find the lowest common ancestors of those ancestors.
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Iteration stops when a unique lowest common ancestor is found.
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The graph origin is necessarily a unique lowest common ancestor.
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Note that None is not an acceptable substitute for NULL_REVISION.
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in the input for this method.
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:param count_steps: If True, the return value will be a tuple of
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(unique_lca, steps) where steps is the number of times that
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find_lca was run. If False, only unique_lca is returned.
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revisions = [left_revision, right_revision]
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lca = self.find_lca(*revisions)
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raise errors.NoCommonAncestor(left_revision, right_revision)
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def iter_topo_order(self, revisions):
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"""Iterate through the input revisions in topological order.
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This sorting only ensures that parents come before their children.
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An ancestor may sort after a descendant if the relationship is not
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visible in the supplied list of revisions.
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sorter = tsort.TopoSorter(self.get_parent_map(revisions))
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return sorter.iter_topo_order()
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def is_ancestor(self, candidate_ancestor, candidate_descendant):
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"""Determine whether a revision is an ancestor of another.
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We answer this using heads() as heads() has the logic to perform the
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smallest number of parent lookups to determine the ancestral
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relationship between N revisions.
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return set([candidate_descendant]) == self.heads(
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[candidate_ancestor, candidate_descendant])
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class HeadsCache(object):
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"""A cache of results for graph heads calls."""
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def __init__(self, graph):
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def heads(self, keys):
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"""Return the heads of keys.
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This matches the API of Graph.heads(), specifically the return value is
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a set which can be mutated, and ordering of the input is not preserved
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:see also: Graph.heads.
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:param keys: The keys to calculate heads for.
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:return: A set containing the heads, which may be mutated without
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affecting future lookups.
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keys = frozenset(keys)
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return set(self._heads[keys])
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heads = self.graph.heads(keys)
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self._heads[keys] = heads
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class _BreadthFirstSearcher(object):
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"""Parallel search breadth-first the ancestry of revisions.
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This class implements the iterator protocol, but additionally
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1. provides a set of seen ancestors, and
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2. allows some ancestries to be unsearched, via stop_searching_any
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def __init__(self, revisions, parents_provider):
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self._next_query = set(revisions)
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self._started_keys = set(self._next_query)
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self._stopped_keys = set()
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self._parents_provider = parents_provider
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self._returning = 'next_with_ghosts'
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self._current_present = set()
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self._current_ghosts = set()
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self._current_parents = {}
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search = '%s=%r' % (prefix, list(self._next_query))
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return ('_BreadthFirstSearcher(iterations=%d, %s,'
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' seen=%r)' % (self._iterations, search, list(self.seen)))
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def get_result(self):
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"""Get a SearchResult for the current state of this searcher.
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:return: A SearchResult for this search so far. The SearchResult is
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static - the search can be advanced and the search result will not
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be invalidated or altered.
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if self._returning == 'next':
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# We have to know the current nodes children to be able to list the
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# exclude keys for them. However, while we could have a second
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# look-ahead result buffer and shuffle things around, this method
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# is typically only called once per search - when memoising the
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# results of the search.
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found, ghosts, next, parents = self._do_query(self._next_query)
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# pretend we didn't query: perhaps we should tweak _do_query to be
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# entirely stateless?
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self.seen.difference_update(next)
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next_query = next.union(ghosts)
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next_query = self._next_query
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excludes = self._stopped_keys.union(next_query)
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included_keys = self.seen.difference(excludes)
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return SearchResult(self._started_keys, excludes, len(included_keys),
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"""Return the next ancestors of this revision.
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Ancestors are returned in the order they are seen in a breadth-first
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traversal. No ancestor will be returned more than once. Ancestors are
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returned before their parentage is queried, so ghosts and missing
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revisions (including the start revisions) are included in the result.
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This can save a round trip in LCA style calculation by allowing
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convergence to be detected without reading the data for the revision
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the convergence occurs on.
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:return: A set of revision_ids.
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if self._returning != 'next':
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# switch to returning the query, not the results.
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self._returning = 'next'
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self._iterations += 1
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if len(self._next_query) == 0:
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raise StopIteration()
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# We have seen what we're querying at this point as we are returning
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# the query, not the results.
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self.seen.update(self._next_query)
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return self._next_query
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def next_with_ghosts(self):
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"""Return the next found ancestors, with ghosts split out.
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Ancestors are returned in the order they are seen in a breadth-first
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traversal. No ancestor will be returned more than once. Ancestors are
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returned only after asking for their parents, which allows us to detect
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which revisions are ghosts and which are not.
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:return: A tuple with (present ancestors, ghost ancestors) sets.
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if self._returning != 'next_with_ghosts':
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# switch to returning the results, not the current query.
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self._returning = 'next_with_ghosts'
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if len(self._next_query) == 0:
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raise StopIteration()
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return self._current_present, self._current_ghosts
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"""Advance the search.
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Updates self.seen, self._next_query, self._current_present,
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self._current_ghosts, self._current_parents and self._iterations.
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self._iterations += 1
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found, ghosts, next, parents = self._do_query(self._next_query)
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self._current_present = found
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self._current_ghosts = ghosts
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self._next_query = next
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self._current_parents = parents
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# ghosts are implicit stop points, otherwise the search cannot be
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# repeated when ghosts are filled.
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self._stopped_keys.update(ghosts)
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def _do_query(self, revisions):
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"""Query for revisions.
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Adds revisions to the seen set.
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:param revisions: Revisions to query.
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:return: A tuple: (set(found_revisions), set(ghost_revisions),
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set(parents_of_found_revisions), dict(found_revisions:parents)).
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found_parents = set()
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parents_of_found = set()
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# revisions may contain nodes that point to other nodes in revisions:
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# we want to filter them out.
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self.seen.update(revisions)
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parent_map = self._parents_provider.get_parent_map(revisions)
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for rev_id, parents in parent_map.iteritems():
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found_parents.add(rev_id)
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parents_of_found.update(p for p in parents if p not in self.seen)
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ghost_parents = revisions - found_parents
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return found_parents, ghost_parents, parents_of_found, parent_map
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def find_seen_ancestors(self, revision):
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"""Find ancestors of this revision that have already been seen."""
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searcher = _BreadthFirstSearcher([revision], self._parents_provider)
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seen_ancestors = set()
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for ancestors in searcher:
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for ancestor in ancestors:
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if ancestor not in self.seen:
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searcher.stop_searching_any([ancestor])
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seen_ancestors.add(ancestor)
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return seen_ancestors
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def stop_searching_any(self, revisions):
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Remove any of the specified revisions from the search list.
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None of the specified revisions are required to be present in the
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search list. In this case, the call is a no-op.
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revisions = frozenset(revisions)
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if self._returning == 'next':
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stopped = self._next_query.intersection(revisions)
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self._next_query = self._next_query.difference(revisions)
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stopped_present = self._current_present.intersection(revisions)
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stopped = stopped_present.union(
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self._current_ghosts.intersection(revisions))
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self._current_present.difference_update(stopped)
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self._current_ghosts.difference_update(stopped)
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# stopping 'x' should stop returning parents of 'x', but
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# not if 'y' always references those same parents
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stop_rev_references = {}
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for rev in stopped_present:
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for parent_id in self._current_parents[rev]:
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if parent_id not in stop_rev_references:
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stop_rev_references[parent_id] = 0
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stop_rev_references[parent_id] += 1
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# if only the stopped revisions reference it, the ref count will be
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for parents in self._current_parents.itervalues():
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for parent_id in parents:
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stop_rev_references[parent_id] -= 1
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for rev_id, refs in stop_rev_references.iteritems():
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stop_parents.add(rev_id)
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self._next_query.difference_update(stop_parents)
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self._stopped_keys.update(stopped)
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def start_searching(self, revisions):
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"""Add revisions to the search.
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The parents of revisions will be returned from the next call to next()
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or next_with_ghosts(). If next_with_ghosts was the most recently used
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next* call then the return value is the result of looking up the
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ghost/not ghost status of revisions. (A tuple (present, ghosted)).
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revisions = frozenset(revisions)
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self._started_keys.update(revisions)
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new_revisions = revisions.difference(self.seen)
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revs, ghosts, query, parents = self._do_query(revisions)
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self._stopped_keys.update(ghosts)
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if self._returning == 'next':
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self._next_query.update(new_revisions)
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# perform a query on revisions
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self._current_present.update(revs)
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self._current_ghosts.update(ghosts)
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self._next_query.update(query)
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self._current_parents.update(parents)
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class SearchResult(object):
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"""The result of a breadth first search.
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A SearchResult provides the ability to reconstruct the search or access a
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set of the keys the search found.
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def __init__(self, start_keys, exclude_keys, key_count, keys):
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"""Create a SearchResult.
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:param start_keys: The keys the search started at.
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:param exclude_keys: The keys the search excludes.
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:param key_count: The total number of keys (from start to but not
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:param keys: The keys the search found. Note that in future we may get
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a SearchResult from a smart server, in which case the keys list is
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not necessarily immediately available.
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self._recipe = (start_keys, exclude_keys, key_count)
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self._keys = frozenset(keys)
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def get_recipe(self):
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"""Return a recipe that can be used to replay this search.
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The recipe allows reconstruction of the same results at a later date
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without knowing all the found keys. The essential elements are a list
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of keys to start and and to stop at. In order to give reproducible
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results when ghosts are encountered by a search they are automatically
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added to the exclude list (or else ghost filling may alter the
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:return: A tuple (start_keys_set, exclude_keys_set, revision_count). To
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recreate the results of this search, create a breadth first
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searcher on the same graph starting at start_keys. Then call next()
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(or next_with_ghosts()) repeatedly, and on every result, call
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stop_searching_any on any keys from the exclude_keys set. The
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revision_count value acts as a trivial cross-check - the found
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revisions of the new search should have as many elements as
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revision_count. If it does not, then additional revisions have been
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ghosted since the search was executed the first time and the second
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"""Return the keys found in this search.
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:return: A set of keys.
added
removed
bzrlib/graph.py
