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# Copyright (C) 2007-2011 Canonical Ltd
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version.
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the Free Software
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# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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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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# Note: DictParentsProvider does not implement get_cached_parent_map
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# Arguably, the data is clearly cached in memory. However, this class
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# is mostly used for testing, and it keeps the tests clean to not
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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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"""A parents provider which stacks (or unions) multiple providers.
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The providers are queries in the order of the provided parent_providers.
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def __init__(self, parent_providers):
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self._parent_providers = parent_providers
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return "%s(%r)" % (self.__class__.__name__, self._parent_providers)
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def get_parent_map(self, keys):
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"""Get a mapping of keys => parents
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A dictionary is returned with an entry for each key present in this
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source. If this source doesn't have information about a key, it should
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[NULL_REVISION] is used as the parent of the first user-committed
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revision. Its parent list is empty.
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:param keys: An iterable returning keys to check (eg revision_ids)
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:return: A dictionary mapping each key to its parents
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# This adds getattr() overhead to each get_parent_map call. However,
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# this is StackedParentsProvider, which means we're dealing with I/O
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# (either local indexes, or remote RPCs), so CPU overhead should be
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for parents_provider in self._parent_providers:
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get_cached = getattr(parents_provider, 'get_cached_parent_map',
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if get_cached is None:
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new_found = get_cached(remaining)
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found.update(new_found)
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remaining.difference_update(new_found)
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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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except errors.UnsupportedOperation:
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found.update(new_found)
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remaining.difference_update(new_found)
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class CachingParentsProvider(object):
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"""A parents provider which will cache the revision => parents as a dict.
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This is useful for providers which have an expensive look up.
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Either a ParentsProvider or a get_parent_map-like callback may be
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supplied. If it provides extra un-asked-for parents, they will be cached,
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but filtered out of get_parent_map.
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The cache is enabled by default, but may be disabled and re-enabled.
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def __init__(self, parent_provider=None, get_parent_map=None):
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:param parent_provider: The ParentProvider to use. It or
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get_parent_map must be supplied.
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:param get_parent_map: The get_parent_map callback to use. It or
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parent_provider must be supplied.
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self._real_provider = parent_provider
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if get_parent_map is None:
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self._get_parent_map = self._real_provider.get_parent_map
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self._get_parent_map = get_parent_map
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self.enable_cache(True)
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return "%s(%r)" % (self.__class__.__name__, self._real_provider)
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def enable_cache(self, cache_misses=True):
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if self._cache is not None:
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raise AssertionError('Cache enabled when already enabled.')
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self._cache_misses = cache_misses
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self.missing_keys = set()
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def disable_cache(self):
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"""Disable and clear the cache."""
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self._cache_misses = None
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self.missing_keys = set()
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def get_cached_map(self):
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"""Return any cached get_parent_map values."""
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if self._cache is None:
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return dict(self._cache)
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def get_cached_parent_map(self, keys):
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"""Return items from the cache.
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This returns the same info as get_parent_map, but explicitly does not
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invoke the supplied ParentsProvider to search for uncached values.
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return dict([(key, cache[key]) for key in keys if key in cache])
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def get_parent_map(self, keys):
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"""See StackedParentsProvider.get_parent_map."""
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cache = self._get_parent_map(keys)
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needed_revisions = set(key for key in keys if key not in cache)
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# Do not ask for negatively cached keys
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needed_revisions.difference_update(self.missing_keys)
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parent_map = self._get_parent_map(needed_revisions)
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cache.update(parent_map)
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if self._cache_misses:
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for key in needed_revisions:
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if key not in parent_map:
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self.note_missing_key(key)
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value = cache.get(key)
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if value is not None:
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def note_missing_key(self, key):
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"""Note that key is a missing key."""
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if self._cache_misses:
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self.missing_keys.add(key)
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class CallableToParentsProviderAdapter(object):
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"""A parents provider that adapts any callable to the parents provider API.
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i.e. it accepts calls to self.get_parent_map and relays them to the
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callable it was constructed with.
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def __init__(self, a_callable):
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self.callable = a_callable
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return "%s(%r)" % (self.__class__.__name__, self.callable)
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def get_parent_map(self, keys):
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return self.callable(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_descendants(self, old_key, new_key):
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"""Find descendants of old_key that are ancestors of new_key."""
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child_map = self.get_child_map(self._find_descendant_ancestors(
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graph = Graph(DictParentsProvider(child_map))
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searcher = graph._make_breadth_first_searcher([old_key])
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def _find_descendant_ancestors(self, old_key, new_key):
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"""Find ancestors of new_key that may be descendants of old_key."""
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stop = self._make_breadth_first_searcher([old_key])
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descendants = self._make_breadth_first_searcher([new_key])
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for revisions in descendants:
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old_stop = stop.seen.intersection(revisions)
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descendants.stop_searching_any(old_stop)
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seen_stop = descendants.find_seen_ancestors(stop.step())
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descendants.stop_searching_any(seen_stop)
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return descendants.seen.difference(stop.seen)
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def get_child_map(self, keys):
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"""Get a mapping from parents to children of the specified keys.
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This is simply the inversion of get_parent_map. Only supplied keys
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will be discovered as children.
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:return: a dict of key:child_list for keys.
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parent_map = self._parents_provider.get_parent_map(keys)
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for child, parents in sorted(parent_map.items()):
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for parent in parents:
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parent_child.setdefault(parent, []).append(child)
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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)
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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 = {cur_tip}
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to_search.update(searching_known_tips)
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parent_map = self.get_parent_map(to_search)
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parents = parent_map.get(cur_tip, None)
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if not parents: # An empty list or None is a ghost
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raise errors.GhostRevisionsHaveNoRevno(target_revision_id,
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for revision_id in searching_known_tips:
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parents = parent_map.get(revision_id, None)
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next_revno = known_revnos[revision_id] - 1
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if next in unknown_searched:
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# We have enough information to return a value right now
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return next_revno + unknown_searched[next]
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if next in known_revnos:
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known_revnos[next] = next_revno
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next_known_tips.append(next)
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searching_known_tips = next_known_tips
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# We reached a known revision, so just add in how many steps it took to
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return known_revnos[cur_tip] + num_steps
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def find_lefthand_distances(self, keys):
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"""Find the distance to null for all the keys in keys.
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:param keys: keys to lookup.
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:return: A dict key->distance for all of keys.
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# Optimisable by concurrent searching, but a random spread should get
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# some sort of hit rate.
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(key, self.find_distance_to_null(key, known_revnos)))
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except errors.GhostRevisionsHaveNoRevno:
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known_revnos.append((key, -1))
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return dict(known_revnos)
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def find_unique_ancestors(self, unique_revision, common_revisions):
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"""Find the unique ancestors for a revision versus others.
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This returns the ancestry of unique_revision, excluding all revisions
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in the ancestry of common_revisions. If unique_revision is in the
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ancestry, then the empty set will be returned.
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:param unique_revision: The revision_id whose ancestry we are
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(XXX: Would this API be better if we allowed multiple revisions on
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to be searched here?)
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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(
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unique_nodes, 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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next(unique_searcher)
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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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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(
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unique_nodes, 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(
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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 = osutils.perf_counter()
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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 = osutils.perf_counter() - 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.values():
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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.
682
step_all_unique_counter = 0
683
# While we still have common nodes to search
684
while common_searcher._next_query:
686
newly_seen_unique) = self._step_unique_and_common_searchers(
687
common_searcher, unique_tip_searchers, unique_searcher)
688
# These nodes are common ancestors of all unique nodes
689
common_to_all_unique_nodes = self._find_nodes_common_to_all_unique(
690
unique_tip_searchers, all_unique_searcher, newly_seen_unique,
691
step_all_unique_counter == 0)
692
step_all_unique_counter = ((step_all_unique_counter + 1)
693
% STEP_UNIQUE_SEARCHER_EVERY)
695
if newly_seen_common:
696
# If a 'common' node is an ancestor of all unique searchers, we
697
# can stop searching it.
698
common_searcher.stop_searching_any(
699
all_unique_searcher.seen.intersection(newly_seen_common))
700
if common_to_all_unique_nodes:
701
common_to_all_unique_nodes.update(
702
common_searcher.find_seen_ancestors(
703
common_to_all_unique_nodes))
704
# The all_unique searcher can start searching the common nodes
705
# but everyone else can stop.
706
# This is the sort of thing where we would like to not have it
707
# start_searching all of the nodes, but only mark all of them
708
# as seen, and have it search only the actual tips. Otherwise
709
# it is another get_parent_map() traversal for it to figure out
710
# what we already should know.
711
all_unique_searcher.start_searching(common_to_all_unique_nodes)
712
common_searcher.stop_searching_any(common_to_all_unique_nodes)
714
next_unique_searchers = self._collapse_unique_searchers(
715
unique_tip_searchers, common_to_all_unique_nodes)
716
if len(unique_tip_searchers) != len(next_unique_searchers):
717
if 'graph' in debug.debug_flags:
718
trace.mutter('Collapsed %d unique searchers => %d'
720
len(unique_tip_searchers),
721
len(next_unique_searchers),
722
all_unique_searcher._iterations)
723
unique_tip_searchers = next_unique_searchers
725
def get_parent_map(self, revisions):
726
"""Get a map of key:parent_list for revisions.
728
This implementation delegates to get_parents, for old parent_providers
729
that do not supply get_parent_map.
732
for rev, parents in self.get_parents(revisions):
733
if parents is not None:
734
result[rev] = parents
737
def _make_breadth_first_searcher(self, revisions):
738
return _BreadthFirstSearcher(revisions, self)
740
def _find_border_ancestors(self, revisions):
741
"""Find common ancestors with at least one uncommon descendant.
743
Border ancestors are identified using a breadth-first
744
search starting at the bottom of the graph. Searches are stopped
745
whenever a node or one of its descendants is determined to be common.
747
This will scale with the number of uncommon ancestors.
749
As well as the border ancestors, a set of seen common ancestors and a
750
list of sets of seen ancestors for each input revision is returned.
751
This allows calculation of graph difference from the results of this
754
if None in revisions:
755
raise errors.InvalidRevisionId(None, self)
756
common_ancestors = set()
757
searchers = [self._make_breadth_first_searcher([r])
759
border_ancestors = set()
763
for searcher in searchers:
764
new_ancestors = searcher.step()
766
newly_seen.update(new_ancestors)
768
for revision in newly_seen:
769
if revision in common_ancestors:
770
# Not a border ancestor because it was seen as common
772
new_common.add(revision)
774
for searcher in searchers:
775
if revision not in searcher.seen:
778
# This is a border because it is a first common that we see
779
# after walking for a while.
780
border_ancestors.add(revision)
781
new_common.add(revision)
783
for searcher in searchers:
784
new_common.update(searcher.find_seen_ancestors(new_common))
785
for searcher in searchers:
786
searcher.start_searching(new_common)
787
common_ancestors.update(new_common)
789
# Figure out what the searchers will be searching next, and if
790
# there is only 1 set being searched, then we are done searching,
791
# since all searchers would have to be searching the same data,
792
# thus it *must* be in common.
793
unique_search_sets = set()
794
for searcher in searchers:
795
will_search_set = frozenset(searcher._next_query)
796
if will_search_set not in unique_search_sets:
797
# This searcher is searching a unique set of nodes, let it
798
unique_search_sets.add(will_search_set)
800
if len(unique_search_sets) == 1:
801
nodes = unique_search_sets.pop()
802
uncommon_nodes = nodes.difference(common_ancestors)
804
raise AssertionError("Somehow we ended up converging"
805
" without actually marking them as"
808
"\nuncommon_nodes: %s"
809
% (revisions, uncommon_nodes))
811
return border_ancestors, common_ancestors, searchers
813
def heads(self, keys):
814
"""Return the heads from amongst keys.
816
This is done by searching the ancestries of each key. Any key that is
817
reachable from another key is not returned; all the others are.
819
This operation scales with the relative depth between any two keys. If
820
any two keys are completely disconnected all ancestry of both sides
823
:param keys: An iterable of keys.
824
:return: A set of the heads. Note that as a set there is no ordering
825
information. Callers will need to filter their input to create
826
order if they need it.
828
candidate_heads = set(keys)
829
if revision.NULL_REVISION in candidate_heads:
830
# NULL_REVISION is only a head if it is the only entry
831
candidate_heads.remove(revision.NULL_REVISION)
832
if not candidate_heads:
833
return {revision.NULL_REVISION}
834
if len(candidate_heads) < 2:
835
return candidate_heads
836
searchers = dict((c, self._make_breadth_first_searcher([c]))
837
for c in candidate_heads)
838
active_searchers = dict(searchers)
839
# skip over the actual candidate for each searcher
840
for searcher in active_searchers.values():
842
# The common walker finds nodes that are common to two or more of the
843
# input keys, so that we don't access all history when a currently
844
# uncommon search point actually meets up with something behind a
845
# common search point. Common search points do not keep searches
846
# active; they just allow us to make searches inactive without
847
# accessing all history.
848
common_walker = self._make_breadth_first_searcher([])
849
while len(active_searchers) > 0:
854
except StopIteration:
855
# No common points being searched at this time.
857
for candidate in list(active_searchers):
859
searcher = active_searchers[candidate]
861
# rare case: we deleted candidate in a previous iteration
862
# through this for loop, because it was determined to be
863
# a descendant of another candidate.
866
ancestors.update(next(searcher))
867
except StopIteration:
868
del active_searchers[candidate]
870
# process found nodes
872
for ancestor in ancestors:
873
if ancestor in candidate_heads:
874
candidate_heads.remove(ancestor)
875
del searchers[ancestor]
876
if ancestor in active_searchers:
877
del active_searchers[ancestor]
878
# it may meet up with a known common node
879
if ancestor in common_walker.seen:
880
# some searcher has encountered our known common nodes:
882
ancestor_set = {ancestor}
883
for searcher in searchers.values():
884
searcher.stop_searching_any(ancestor_set)
886
# or it may have been just reached by all the searchers:
887
for searcher in searchers.values():
888
if ancestor not in searcher.seen:
891
# The final active searcher has just reached this node,
892
# making it be known as a descendant of all candidates,
893
# so we can stop searching it, and any seen ancestors
894
new_common.add(ancestor)
895
for searcher in searchers.values():
897
searcher.find_seen_ancestors([ancestor])
898
searcher.stop_searching_any(seen_ancestors)
899
common_walker.start_searching(new_common)
900
return candidate_heads
902
def find_merge_order(self, tip_revision_id, lca_revision_ids):
903
"""Find the order that each revision was merged into tip.
905
This basically just walks backwards with a stack, and walks left-first
906
until it finds a node to stop.
908
if len(lca_revision_ids) == 1:
909
return list(lca_revision_ids)
910
looking_for = set(lca_revision_ids)
911
# TODO: Is there a way we could do this "faster" by batching up the
912
# get_parent_map requests?
913
# TODO: Should we also be culling the ancestry search right away? We
914
# could add looking_for to the "stop" list, and walk their
915
# ancestry in batched mode. The flip side is it might mean we walk a
916
# lot of "stop" nodes, rather than only the minimum.
917
# Then again, without it we may trace back into ancestry we could have
919
stack = [tip_revision_id]
922
while stack and looking_for:
925
if next in looking_for:
927
looking_for.remove(next)
928
if len(looking_for) == 1:
929
found.append(looking_for.pop())
932
parent_ids = self.get_parent_map([next]).get(next, None)
933
if not parent_ids: # Ghost, nothing to search here
935
for parent_id in reversed(parent_ids):
936
# TODO: (performance) We see the parent at this point, but we
937
# wait to mark it until later to make sure we get left
938
# parents before right parents. However, instead of
939
# waiting until we have traversed enough parents, we
940
# could instead note that we've found it, and once all
941
# parents are in the stack, just reverse iterate the
943
if parent_id not in stop:
944
# this will need to be searched
945
stack.append(parent_id)
949
def find_lefthand_merger(self, merged_key, tip_key):
950
"""Find the first lefthand ancestor of tip_key that merged merged_key.
952
We do this by first finding the descendants of merged_key, then
953
walking through the lefthand ancestry of tip_key until we find a key
954
that doesn't descend from merged_key. Its child is the key that
957
:return: The first lefthand ancestor of tip_key to merge merged_key.
958
merged_key if it is a lefthand ancestor of tip_key.
959
None if no ancestor of tip_key merged merged_key.
961
descendants = self.find_descendants(merged_key, tip_key)
962
candidate_iterator = self.iter_lefthand_ancestry(tip_key)
963
last_candidate = None
964
for candidate in candidate_iterator:
965
if candidate not in descendants:
966
return last_candidate
967
last_candidate = candidate
969
def find_unique_lca(self, left_revision, right_revision,
971
"""Find a unique LCA.
973
Find lowest common ancestors. If there is no unique common
974
ancestor, find the lowest common ancestors of those ancestors.
976
Iteration stops when a unique lowest common ancestor is found.
977
The graph origin is necessarily a unique lowest common ancestor.
979
Note that None is not an acceptable substitute for NULL_REVISION.
980
in the input for this method.
982
:param count_steps: If True, the return value will be a tuple of
983
(unique_lca, steps) where steps is the number of times that
984
find_lca was run. If False, only unique_lca is returned.
986
revisions = [left_revision, right_revision]
990
lca = self.find_lca(*revisions)
998
raise errors.NoCommonAncestor(left_revision, right_revision)
1001
def iter_ancestry(self, revision_ids):
1002
"""Iterate the ancestry of this revision.
1004
:param revision_ids: Nodes to start the search
1005
:return: Yield tuples mapping a revision_id to its parents for the
1006
ancestry of revision_id.
1007
Ghosts will be returned with None as their parents, and nodes
1008
with no parents will have NULL_REVISION as their only parent. (As
1009
defined by get_parent_map.)
1010
There will also be a node for (NULL_REVISION, ())
1012
pending = set(revision_ids)
1015
processed.update(pending)
1016
next_map = self.get_parent_map(pending)
1017
next_pending = set()
1018
for item in next_map.items():
1020
next_pending.update(p for p in item[1] if p not in processed)
1021
ghosts = pending.difference(next_map)
1022
for ghost in ghosts:
1024
pending = next_pending
1026
def iter_lefthand_ancestry(self, start_key, stop_keys=None):
1027
if stop_keys is None:
1029
next_key = start_key
1031
def get_parents(key):
1033
return self._parents_provider.get_parent_map([key])[key]
1035
raise errors.RevisionNotPresent(next_key, self)
1037
if next_key in stop_keys:
1039
parents = get_parents(next_key)
1041
if len(parents) == 0:
1044
next_key = parents[0]
1046
def iter_topo_order(self, revisions):
1047
"""Iterate through the input revisions in topological order.
1049
This sorting only ensures that parents come before their children.
1050
An ancestor may sort after a descendant if the relationship is not
1051
visible in the supplied list of revisions.
1053
from breezy import tsort
1054
sorter = tsort.TopoSorter(self.get_parent_map(revisions))
1055
return sorter.iter_topo_order()
1057
def is_ancestor(self, candidate_ancestor, candidate_descendant):
1058
"""Determine whether a revision is an ancestor of another.
1060
We answer this using heads() as heads() has the logic to perform the
1061
smallest number of parent lookups to determine the ancestral
1062
relationship between N revisions.
1064
return {candidate_descendant} == self.heads(
1065
[candidate_ancestor, candidate_descendant])
1067
def is_between(self, revid, lower_bound_revid, upper_bound_revid):
1068
"""Determine whether a revision is between two others.
1070
returns true if and only if:
1071
lower_bound_revid <= revid <= upper_bound_revid
1073
return ((upper_bound_revid is None or
1074
self.is_ancestor(revid, upper_bound_revid)) and
1075
(lower_bound_revid is None or
1076
self.is_ancestor(lower_bound_revid, revid)))
1078
def _search_for_extra_common(self, common, searchers):
1079
"""Make sure that unique nodes are genuinely unique.
1081
After _find_border_ancestors, all nodes marked "common" are indeed
1082
common. Some of the nodes considered unique are not, due to history
1083
shortcuts stopping the searches early.
1085
We know that we have searched enough when all common search tips are
1086
descended from all unique (uncommon) nodes because we know that a node
1087
cannot be an ancestor of its own ancestor.
1089
:param common: A set of common nodes
1090
:param searchers: The searchers returned from _find_border_ancestors
1093
# Basic algorithm...
1094
# A) The passed in searchers should all be on the same tips, thus
1095
# they should be considered the "common" searchers.
1096
# B) We find the difference between the searchers, these are the
1097
# "unique" nodes for each side.
1098
# C) We do a quick culling so that we only start searching from the
1099
# more interesting unique nodes. (A unique ancestor is more
1100
# interesting than any of its children.)
1101
# D) We start searching for ancestors common to all unique nodes.
1102
# E) We have the common searchers stop searching any ancestors of
1103
# nodes found by (D)
1104
# F) When there are no more common search tips, we stop
1106
# TODO: We need a way to remove unique_searchers when they overlap with
1107
# other unique searchers.
1108
if len(searchers) != 2:
1109
raise NotImplementedError(
1110
"Algorithm not yet implemented for > 2 searchers")
1111
common_searchers = searchers
1112
left_searcher = searchers[0]
1113
right_searcher = searchers[1]
1114
unique = left_searcher.seen.symmetric_difference(right_searcher.seen)
1115
if not unique: # No unique nodes, nothing to do
1117
total_unique = len(unique)
1118
unique = self._remove_simple_descendants(unique,
1119
self.get_parent_map(unique))
1120
simple_unique = len(unique)
1122
unique_searchers = []
1123
for revision_id in unique:
1124
if revision_id in left_searcher.seen:
1125
parent_searcher = left_searcher
1127
parent_searcher = right_searcher
1128
revs_to_search = parent_searcher.find_seen_ancestors([revision_id])
1129
if not revs_to_search: # XXX: This shouldn't be possible
1130
revs_to_search = [revision_id]
1131
searcher = self._make_breadth_first_searcher(revs_to_search)
1132
# We don't care about the starting nodes.
1134
unique_searchers.append(searcher)
1136
# possible todo: aggregate the common searchers into a single common
1137
# searcher, just make sure that we include the nodes into the .seen
1138
# properties of the original searchers
1140
ancestor_all_unique = None
1141
for searcher in unique_searchers:
1142
if ancestor_all_unique is None:
1143
ancestor_all_unique = set(searcher.seen)
1145
ancestor_all_unique = ancestor_all_unique.intersection(
1148
trace.mutter('Started %d unique searchers for %d unique revisions',
1149
simple_unique, total_unique)
1151
while True: # If we have no more nodes we have nothing to do
1152
newly_seen_common = set()
1153
for searcher in common_searchers:
1154
newly_seen_common.update(searcher.step())
1155
newly_seen_unique = set()
1156
for searcher in unique_searchers:
1157
newly_seen_unique.update(searcher.step())
1158
new_common_unique = set()
1159
for revision in newly_seen_unique:
1160
for searcher in unique_searchers:
1161
if revision not in searcher.seen:
1164
# This is a border because it is a first common that we see
1165
# after walking for a while.
1166
new_common_unique.add(revision)
1167
if newly_seen_common:
1168
# These are nodes descended from one of the 'common' searchers.
1169
# Make sure all searchers are on the same page
1170
for searcher in common_searchers:
1171
newly_seen_common.update(
1172
searcher.find_seen_ancestors(newly_seen_common))
1173
# We start searching the whole ancestry. It is a bit wasteful,
1174
# though. We really just want to mark all of these nodes as
1175
# 'seen' and then start just the tips. However, it requires a
1176
# get_parent_map() call to figure out the tips anyway, and all
1177
# redundant requests should be fairly fast.
1178
for searcher in common_searchers:
1179
searcher.start_searching(newly_seen_common)
1181
# If a 'common' node is an ancestor of all unique searchers, we
1182
# can stop searching it.
1183
stop_searching_common = ancestor_all_unique.intersection(
1185
if stop_searching_common:
1186
for searcher in common_searchers:
1187
searcher.stop_searching_any(stop_searching_common)
1188
if new_common_unique:
1189
# We found some ancestors that are common
1190
for searcher in unique_searchers:
1191
new_common_unique.update(
1192
searcher.find_seen_ancestors(new_common_unique))
1193
# Since these are common, we can grab another set of ancestors
1195
for searcher in common_searchers:
1196
new_common_unique.update(
1197
searcher.find_seen_ancestors(new_common_unique))
1199
# We can tell all of the unique searchers to start at these
1200
# nodes, and tell all of the common searchers to *stop*
1201
# searching these nodes
1202
for searcher in unique_searchers:
1203
searcher.start_searching(new_common_unique)
1204
for searcher in common_searchers:
1205
searcher.stop_searching_any(new_common_unique)
1206
ancestor_all_unique.update(new_common_unique)
1208
# Filter out searchers that don't actually search different
1209
# nodes. We already have the ancestry intersection for them
1210
next_unique_searchers = []
1211
unique_search_sets = set()
1212
for searcher in unique_searchers:
1213
will_search_set = frozenset(searcher._next_query)
1214
if will_search_set not in unique_search_sets:
1215
# This searcher is searching a unique set of nodes, let
1217
unique_search_sets.add(will_search_set)
1218
next_unique_searchers.append(searcher)
1219
unique_searchers = next_unique_searchers
1220
for searcher in common_searchers:
1221
if searcher._next_query:
1224
# All common searcher have stopped searching
1227
def _remove_simple_descendants(self, revisions, parent_map):
1228
"""remove revisions which are children of other ones in the set
1230
This doesn't do any graph searching, it just checks the immediate
1231
parent_map to find if there are any children which can be removed.
1233
:param revisions: A set of revision_ids
1234
:return: A set of revision_ids with the children removed
1236
simple_ancestors = revisions.copy()
1237
# TODO: jam 20071214 we *could* restrict it to searching only the
1238
# parent_map of revisions already present in 'revisions', but
1239
# considering the general use case, I think this is actually
1242
# This is the same as the following loop. I don't know that it is any
1244
# simple_ancestors.difference_update(r for r, p_ids in parent_map.iteritems()
1245
# if p_ids is not None and revisions.intersection(p_ids))
1246
# return simple_ancestors
1248
# Yet Another Way, invert the parent map (which can be cached)
1250
# for revision_id, parent_ids in parent_map.iteritems():
1251
# for p_id in parent_ids:
1252
## descendants.setdefault(p_id, []).append(revision_id)
1253
# for revision in revisions.intersection(descendants):
1254
# simple_ancestors.difference_update(descendants[revision])
1255
# return simple_ancestors
1256
for revision, parent_ids in parent_map.items():
1257
if parent_ids is None:
1259
for parent_id in parent_ids:
1260
if parent_id in revisions:
1261
# This node has a parent present in the set, so we can
1263
simple_ancestors.discard(revision)
1265
return simple_ancestors
1268
class HeadsCache(object):
1269
"""A cache of results for graph heads calls."""
1271
def __init__(self, graph):
1275
def heads(self, keys):
1276
"""Return the heads of keys.
1278
This matches the API of Graph.heads(), specifically the return value is
1279
a set which can be mutated, and ordering of the input is not preserved
1282
:see also: Graph.heads.
1283
:param keys: The keys to calculate heads for.
1284
:return: A set containing the heads, which may be mutated without
1285
affecting future lookups.
1287
keys = frozenset(keys)
1289
return set(self._heads[keys])
1291
heads = self.graph.heads(keys)
1292
self._heads[keys] = heads
1296
class FrozenHeadsCache(object):
1297
"""Cache heads() calls, assuming the caller won't modify them."""
1299
def __init__(self, graph):
1303
def heads(self, keys):
1304
"""Return the heads of keys.
1306
Similar to Graph.heads(). The main difference is that the return value
1307
is a frozen set which cannot be mutated.
1309
:see also: Graph.heads.
1310
:param keys: The keys to calculate heads for.
1311
:return: A frozenset containing the heads.
1313
keys = frozenset(keys)
1315
return self._heads[keys]
1317
heads = frozenset(self.graph.heads(keys))
1318
self._heads[keys] = heads
1321
def cache(self, keys, heads):
1322
"""Store a known value."""
1323
self._heads[frozenset(keys)] = frozenset(heads)
1326
class _BreadthFirstSearcher(object):
1327
"""Parallel search breadth-first the ancestry of revisions.
1329
This class implements the iterator protocol, but additionally
1330
1. provides a set of seen ancestors, and
1331
2. allows some ancestries to be unsearched, via stop_searching_any
1334
def __init__(self, revisions, parents_provider):
1335
self._iterations = 0
1336
self._next_query = set(revisions)
1338
self._started_keys = set(self._next_query)
1339
self._stopped_keys = set()
1340
self._parents_provider = parents_provider
1341
self._returning = 'next_with_ghosts'
1342
self._current_present = set()
1343
self._current_ghosts = set()
1344
self._current_parents = {}
1347
if self._iterations:
1348
prefix = "searching"
1351
search = '%s=%r' % (prefix, list(self._next_query))
1352
return ('_BreadthFirstSearcher(iterations=%d, %s,'
1353
' seen=%r)' % (self._iterations, search, list(self.seen)))
1355
def get_state(self):
1356
"""Get the current state of this searcher.
1358
:return: Tuple with started keys, excludes and included keys
1360
if self._returning == 'next':
1361
# We have to know the current nodes children to be able to list the
1362
# exclude keys for them. However, while we could have a second
1363
# look-ahead result buffer and shuffle things around, this method
1364
# is typically only called once per search - when memoising the
1365
# results of the search.
1366
found, ghosts, next, parents = self._do_query(self._next_query)
1367
# pretend we didn't query: perhaps we should tweak _do_query to be
1368
# entirely stateless?
1369
self.seen.difference_update(next)
1370
next_query = next.union(ghosts)
1372
next_query = self._next_query
1373
excludes = self._stopped_keys.union(next_query)
1374
included_keys = self.seen.difference(excludes)
1375
return self._started_keys, excludes, included_keys
1380
except StopIteration:
1384
"""Return the next ancestors of this revision.
1386
Ancestors are returned in the order they are seen in a breadth-first
1387
traversal. No ancestor will be returned more than once. Ancestors are
1388
returned before their parentage is queried, so ghosts and missing
1389
revisions (including the start revisions) are included in the result.
1390
This can save a round trip in LCA style calculation by allowing
1391
convergence to be detected without reading the data for the revision
1392
the convergence occurs on.
1394
:return: A set of revision_ids.
1396
if self._returning != 'next':
1397
# switch to returning the query, not the results.
1398
self._returning = 'next'
1399
self._iterations += 1
1402
if len(self._next_query) == 0:
1403
raise StopIteration()
1404
# We have seen what we're querying at this point as we are returning
1405
# the query, not the results.
1406
self.seen.update(self._next_query)
1407
return self._next_query
1411
def next_with_ghosts(self):
1412
"""Return the next found ancestors, with ghosts split out.
1414
Ancestors are returned in the order they are seen in a breadth-first
1415
traversal. No ancestor will be returned more than once. Ancestors are
1416
returned only after asking for their parents, which allows us to detect
1417
which revisions are ghosts and which are not.
1419
:return: A tuple with (present ancestors, ghost ancestors) sets.
1421
if self._returning != 'next_with_ghosts':
1422
# switch to returning the results, not the current query.
1423
self._returning = 'next_with_ghosts'
1425
if len(self._next_query) == 0:
1426
raise StopIteration()
1428
return self._current_present, self._current_ghosts
1431
"""Advance the search.
1433
Updates self.seen, self._next_query, self._current_present,
1434
self._current_ghosts, self._current_parents and self._iterations.
1436
self._iterations += 1
1437
found, ghosts, next, parents = self._do_query(self._next_query)
1438
self._current_present = found
1439
self._current_ghosts = ghosts
1440
self._next_query = next
1441
self._current_parents = parents
1442
# ghosts are implicit stop points, otherwise the search cannot be
1443
# repeated when ghosts are filled.
1444
self._stopped_keys.update(ghosts)
1446
def _do_query(self, revisions):
1447
"""Query for revisions.
1449
Adds revisions to the seen set.
1451
:param revisions: Revisions to query.
1452
:return: A tuple: (set(found_revisions), set(ghost_revisions),
1453
set(parents_of_found_revisions), dict(found_revisions:parents)).
1455
found_revisions = set()
1456
parents_of_found = set()
1457
# revisions may contain nodes that point to other nodes in revisions:
1458
# we want to filter them out.
1460
seen.update(revisions)
1461
parent_map = self._parents_provider.get_parent_map(revisions)
1462
found_revisions.update(parent_map)
1463
for rev_id, parents in parent_map.items():
1466
new_found_parents = [p for p in parents if p not in seen]
1467
if new_found_parents:
1468
# Calling set.update() with an empty generator is actually
1470
parents_of_found.update(new_found_parents)
1471
ghost_revisions = revisions - found_revisions
1472
return found_revisions, ghost_revisions, parents_of_found, parent_map
1477
def find_seen_ancestors(self, revisions):
1478
"""Find ancestors of these revisions that have already been seen.
1480
This function generally makes the assumption that querying for the
1481
parents of a node that has already been queried is reasonably cheap.
1482
(eg, not a round trip to a remote host).
1484
# TODO: Often we might ask one searcher for its seen ancestors, and
1485
# then ask another searcher the same question. This can result in
1486
# searching the same revisions repeatedly if the two searchers
1487
# have a lot of overlap.
1488
all_seen = self.seen
1489
pending = set(revisions).intersection(all_seen)
1490
seen_ancestors = set(pending)
1492
if self._returning == 'next':
1493
# self.seen contains what nodes have been returned, not what nodes
1494
# have been queried. We don't want to probe for nodes that haven't
1495
# been searched yet.
1496
not_searched_yet = self._next_query
1498
not_searched_yet = ()
1499
pending.difference_update(not_searched_yet)
1500
get_parent_map = self._parents_provider.get_parent_map
1502
parent_map = get_parent_map(pending)
1504
# We don't care if it is a ghost, since it can't be seen if it is
1506
for parent_ids in parent_map.values():
1507
all_parents.extend(parent_ids)
1508
next_pending = all_seen.intersection(
1509
all_parents).difference(seen_ancestors)
1510
seen_ancestors.update(next_pending)
1511
next_pending.difference_update(not_searched_yet)
1512
pending = next_pending
1514
return seen_ancestors
1516
def stop_searching_any(self, revisions):
1518
Remove any of the specified revisions from the search list.
1520
None of the specified revisions are required to be present in the
1523
It is okay to call stop_searching_any() for revisions which were seen
1524
in previous iterations. It is the callers responsibility to call
1525
find_seen_ancestors() to make sure that current search tips that are
1526
ancestors of those revisions are also stopped. All explicitly stopped
1527
revisions will be excluded from the search result's get_keys(), though.
1529
# TODO: does this help performance?
1532
revisions = frozenset(revisions)
1533
if self._returning == 'next':
1534
stopped = self._next_query.intersection(revisions)
1535
self._next_query = self._next_query.difference(revisions)
1537
stopped_present = self._current_present.intersection(revisions)
1538
stopped = stopped_present.union(
1539
self._current_ghosts.intersection(revisions))
1540
self._current_present.difference_update(stopped)
1541
self._current_ghosts.difference_update(stopped)
1542
# stopping 'x' should stop returning parents of 'x', but
1543
# not if 'y' always references those same parents
1544
stop_rev_references = {}
1545
for rev in stopped_present:
1546
for parent_id in self._current_parents[rev]:
1547
if parent_id not in stop_rev_references:
1548
stop_rev_references[parent_id] = 0
1549
stop_rev_references[parent_id] += 1
1550
# if only the stopped revisions reference it, the ref count will be
1552
for parents in self._current_parents.values():
1553
for parent_id in parents:
1555
stop_rev_references[parent_id] -= 1
1558
stop_parents = set()
1559
for rev_id, refs in stop_rev_references.items():
1561
stop_parents.add(rev_id)
1562
self._next_query.difference_update(stop_parents)
1563
self._stopped_keys.update(stopped)
1564
self._stopped_keys.update(revisions)
1567
def start_searching(self, revisions):
1568
"""Add revisions to the search.
1570
The parents of revisions will be returned from the next call to next()
1571
or next_with_ghosts(). If next_with_ghosts was the most recently used
1572
next* call then the return value is the result of looking up the
1573
ghost/not ghost status of revisions. (A tuple (present, ghosted)).
1575
revisions = frozenset(revisions)
1576
self._started_keys.update(revisions)
1577
new_revisions = revisions.difference(self.seen)
1578
if self._returning == 'next':
1579
self._next_query.update(new_revisions)
1580
self.seen.update(new_revisions)
1582
# perform a query on revisions
1583
revs, ghosts, query, parents = self._do_query(revisions)
1584
self._stopped_keys.update(ghosts)
1585
self._current_present.update(revs)
1586
self._current_ghosts.update(ghosts)
1587
self._next_query.update(query)
1588
self._current_parents.update(parents)
1592
def invert_parent_map(parent_map):
1593
"""Given a map from child => parents, create a map of parent=>children"""
1595
for child, parents in parent_map.items():
1597
# Any given parent is likely to have only a small handful
1598
# of children, many will have only one. So we avoid mem overhead of
1599
# a list, in exchange for extra copying of tuples
1600
if p not in child_map:
1601
child_map[p] = (child,)
1603
child_map[p] = child_map[p] + (child,)
1607
def collapse_linear_regions(parent_map):
1608
"""Collapse regions of the graph that are 'linear'.
1614
can be collapsed by removing B and getting::
1618
:param parent_map: A dictionary mapping children to their parents
1619
:return: Another dictionary with 'linear' chains collapsed
1621
# Note: this isn't a strictly minimal collapse. For example:
1629
# Will not have 'D' removed, even though 'E' could fit. Also:
1635
# A and C are both kept because they are edges of the graph. We *could* get
1636
# rid of A if we wanted.
1644
# Will not have any nodes removed, even though you do have an
1645
# 'uninteresting' linear D->B and E->C
1647
for child, parents in parent_map.items():
1648
children.setdefault(child, [])
1650
children.setdefault(p, []).append(child)
1653
result = dict(parent_map)
1654
for node in parent_map:
1655
parents = result[node]
1656
if len(parents) == 1:
1657
parent_children = children[parents[0]]
1658
if len(parent_children) != 1:
1659
# This is not the only child
1661
node_children = children[node]
1662
if len(node_children) != 1:
1664
child_parents = result.get(node_children[0], None)
1665
if len(child_parents) != 1:
1666
# This is not its only parent
1668
# The child of this node only points at it, and the parent only has
1669
# this as a child. remove this node, and join the others together
1670
result[node_children[0]] = parents
1671
children[parents[0]] = node_children
1679
class GraphThunkIdsToKeys(object):
1680
"""Forwards calls about 'ids' to be about keys internally."""
1682
def __init__(self, graph):
1685
def topo_sort(self):
1686
return [r for (r,) in self._graph.topo_sort()]
1688
def heads(self, ids):
1689
"""See Graph.heads()"""
1690
as_keys = [(i,) for i in ids]
1691
head_keys = self._graph.heads(as_keys)
1692
return {h[0] for h in head_keys}
1694
def merge_sort(self, tip_revision):
1695
nodes = self._graph.merge_sort((tip_revision,))
1697
node.key = node.key[0]
1700
def add_node(self, revision, parents):
1701
self._graph.add_node((revision,), [(p,) for p in parents])
1704
_counters = [0, 0, 0, 0, 0, 0, 0]
1706
from ._known_graph_pyx import KnownGraph
1707
except ImportError as e:
1708
osutils.failed_to_load_extension(e)
1709
from ._known_graph_py import KnownGraph # noqa: F401
added
removed
breezy/graph.py
