# Copyright (C) 2005, 2006, 2008 Canonical Ltd # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA """Topological sorting routines.""" from __future__ import absolute_import from bzrlib import ( errors, graph as _mod_graph, revision as _mod_revision, ) __all__ = ["topo_sort", "TopoSorter", "merge_sort", "MergeSorter"] def topo_sort(graph): """Topological sort a graph. graph -- sequence of pairs of node->parents_list. The result is a list of node names, such that all parents come before their children. node identifiers can be any hashable object, and are typically strings. This function has the same purpose as the TopoSorter class, but uses a different algorithm to sort the graph. That means that while both return a list with parents before their child nodes, the exact ordering can be different. topo_sort is faster when the whole list is needed, while when iterating over a part of the list, TopoSorter.iter_topo_order should be used. """ kg = _mod_graph.KnownGraph(dict(graph)) return kg.topo_sort() class TopoSorter(object): def __init__(self, graph): """Topological sorting of a graph. :param graph: sequence of pairs of node_name->parent_names_list. i.e. [('C', ['B']), ('B', ['A']), ('A', [])] For this input the output from the sort or iter_topo_order routines will be: 'A', 'B', 'C' node identifiers can be any hashable object, and are typically strings. If you have a graph like [('a', ['b']), ('a', ['c'])] this will only use one of the two values for 'a'. The graph is sorted lazily: until you iterate or sort the input is not processed other than to create an internal representation. iteration or sorting may raise GraphCycleError if a cycle is present in the graph. """ # store a dict of the graph. self._graph = dict(graph) def sorted(self): """Sort the graph and return as a list. After calling this the sorter is empty and you must create a new one. """ return list(self.iter_topo_order()) ### Useful if fiddling with this code. ### # cross check ### sorted_names = list(self.iter_topo_order()) ### for index in range(len(sorted_names)): ### rev = sorted_names[index] ### for left_index in range(index): ### if rev in self.original_graph[sorted_names[left_index]]: ### print "revision in parent list of earlier revision" ### import pdb;pdb.set_trace() def iter_topo_order(self): """Yield the nodes of the graph in a topological order. After finishing iteration the sorter is empty and you cannot continue iteration. """ graph = self._graph visitable = set(graph) # this is a stack storing the depth first search into the graph. pending_node_stack = [] # at each level of 'recursion' we have to check each parent. This # stack stores the parents we have not yet checked for the node at the # matching depth in pending_node_stack pending_parents_stack = [] # this is a set of the completed nodes for fast checking whether a # parent in a node we are processing on the stack has already been # emitted and thus can be skipped. completed_node_names = set() while graph: # now pick a random node in the source graph, and transfer it to the # top of the depth first search stack of pending nodes. node_name, parents = graph.popitem() pending_node_stack.append(node_name) pending_parents_stack.append(list(parents)) # loop until pending_node_stack is empty while pending_node_stack: parents_to_visit = pending_parents_stack[-1] # if there are no parents left, the revision is done if not parents_to_visit: # append the revision to the topo sorted list # all the nodes parents have been added to the output, # now we can add it to the output. popped_node = pending_node_stack.pop() pending_parents_stack.pop() completed_node_names.add(popped_node) yield popped_node else: # recurse depth first into a single parent next_node_name = parents_to_visit.pop() if next_node_name in completed_node_names: # parent was already completed by a child, skip it. continue if next_node_name not in visitable: # parent is not a node in the original graph, skip it. continue # transfer it along with its parents from the source graph # into the top of the current depth first search stack. try: parents = graph.pop(next_node_name) except KeyError: # if the next node is not in the source graph it has # already been popped from it and placed into the # current search stack (but not completed or we would # have hit the continue 6 lines up). this indicates a # cycle. raise errors.GraphCycleError(pending_node_stack) pending_node_stack.append(next_node_name) pending_parents_stack.append(list(parents)) def merge_sort(graph, branch_tip, mainline_revisions=None, generate_revno=False): """Topological sort a graph which groups merges. :param graph: sequence of pairs of node->parents_list. :param branch_tip: the tip of the branch to graph. Revisions not reachable from branch_tip are not included in the output. :param mainline_revisions: If not None this forces a mainline to be used rather than synthesised from the graph. This must be a valid path through some part of the graph. If the mainline does not cover all the revisions, output stops at the start of the old revision listed in the mainline revisions list. The order for this parameter is oldest-first. :param generate_revno: Optional parameter controlling the generation of revision number sequences in the output. See the output description of the MergeSorter docstring for details. :result: See the MergeSorter docstring for details. Node identifiers can be any hashable object, and are typically strings. """ return MergeSorter(graph, branch_tip, mainline_revisions, generate_revno).sorted() class MergeSorter(object): __slots__ = ['_node_name_stack', '_node_merge_depth_stack', '_pending_parents_stack', '_first_child_stack', '_left_subtree_pushed_stack', '_generate_revno', '_graph', '_mainline_revisions', '_stop_revision', '_original_graph', '_revnos', '_revno_to_branch_count', '_completed_node_names', '_scheduled_nodes', ] def __init__(self, graph, branch_tip, mainline_revisions=None, generate_revno=False): """Merge-aware topological sorting of a graph. :param graph: sequence of pairs of node_name->parent_names_list. i.e. [('C', ['B']), ('B', ['A']), ('A', [])] For this input the output from the sort or iter_topo_order routines will be: 'A', 'B', 'C' :param branch_tip: the tip of the branch to graph. Revisions not reachable from branch_tip are not included in the output. :param mainline_revisions: If not None this forces a mainline to be used rather than synthesised from the graph. This must be a valid path through some part of the graph. If the mainline does not cover all the revisions, output stops at the start of the old revision listed in the mainline revisions list. The order for this parameter is oldest-first. :param generate_revno: Optional parameter controlling the generation of revision number sequences in the output. See the output description for more details. The result is a list sorted so that all parents come before their children. Each element of the list is a tuple containing: (sequence_number, node_name, merge_depth, end_of_merge) * sequence_number: The sequence of this row in the output. Useful for GUIs. * node_name: The node name: opaque text to the merge routine. * merge_depth: How many levels of merging deep this node has been found. * revno_sequence: When requested this field provides a sequence of revision numbers for all revisions. The format is: (REVNO, BRANCHNUM, BRANCHREVNO). BRANCHNUM is the number of the branch that the revno is on. From left to right the REVNO numbers are the sequence numbers within that branch of the revision. For instance, the graph {A:[], B:['A'], C:['A', 'B']} will get the following revno_sequences assigned: A:(1,), B:(1,1,1), C:(2,). This should be read as 'A is the first commit in the trunk', 'B is the first commit on the first branch made from A', 'C is the second commit in the trunk'. * end_of_merge: When True the next node is part of a different merge. node identifiers can be any hashable object, and are typically strings. If you have a graph like [('a', ['b']), ('a', ['c'])] this will only use one of the two values for 'a'. The graph is sorted lazily: until you iterate or sort the input is not processed other than to create an internal representation. iteration or sorting may raise GraphCycleError if a cycle is present in the graph. Background information on the design: ------------------------------------- definition: the end of any cluster or 'merge' occurs when: 1 - the next revision has a lower merge depth than we do. i.e. A 0 B 1 C 2 D 1 E 0 C, D are the ends of clusters, E might be but we need more data. 2 - or the next revision at our merge depth is not our left most ancestor. This is required to handle multiple-merges in one commit. i.e. A 0 [F, B, E] B 1 [D, C] C 2 [D] D 1 [F] E 1 [F] F 0 C is the end of a cluster due to rule 1. D is not the end of a cluster from rule 1, but is from rule 2: E is not its left most ancestor E is the end of a cluster due to rule 1 F might be but we need more data. we show connecting lines to a parent when: - The parent is the start of a merge within this cluster. That is, the merge was not done to the mainline before this cluster was merged to the mainline. This can be detected thus: * The parent has a higher merge depth and is the next revision in the list. The next revision in the list constraint is needed for this case: A 0 [D, B] B 1 [C, F] # we do not want to show a line to F which is depth 2 but not a merge C 1 [H] # note that this is a long line to show back to the ancestor - see the end of merge rules. D 0 [G, E] E 1 [G, F] F 2 [G] G 1 [H] H 0 - Part of this merges 'branch': The parent has the same merge depth and is our left most parent and we are not the end of the cluster. A 0 [C, B] lines: [B, C] B 1 [E, C] lines: [C] C 0 [D] lines: [D] D 0 [F, E] lines: [E, F] E 1 [F] lines: [F] F 0 - The end of this merge/cluster: we can ONLY have multiple parents at the end of a cluster if this branch was previously merged into the 'mainline'. - if we have one and only one parent, show it Note that this may be to a greater merge depth - for instance if this branch continued from a deeply nested branch to add something to it. - if we have more than one parent - show the second oldest (older == further down the list) parent with an equal or lower merge depth XXXX revisit when awake. ddaa asks about the relevance of each one - maybe more than one parent is relevant """ self._generate_revno = generate_revno # a dict of the graph. self._graph = dict(graph) # if there is an explicit mainline, alter the graph to match. This is # easier than checking at every merge whether we are on the mainline and # if so which path to take. if mainline_revisions is None: self._mainline_revisions = [] self._stop_revision = None else: self._mainline_revisions = list(mainline_revisions) self._stop_revision = self._mainline_revisions[0] # skip the first revision, its what we reach and its parents are # therefore irrelevant for index, revision in enumerate(self._mainline_revisions[1:]): # NB: index 0 means self._mainline_revisions[1] # if the mainline matches the graph, nothing to do. parent = self._mainline_revisions[index] if parent is None: # end of mainline_revisions history continue graph_parent_ids = self._graph[revision] if not graph_parent_ids: # We ran into a ghost, skip over it, this is a workaround for # bug #243536, the _graph has had ghosts stripped, but the # mainline_revisions have not continue if graph_parent_ids[0] == parent: continue # remove it from its prior spot self._graph[revision].remove(parent) # insert it into the start of the mainline self._graph[revision].insert(0, parent) # we need to do a check late in the process to detect end-of-merges # which requires the parents to be accessible: its easier for now # to just keep the original graph around. self._original_graph = dict(self._graph.items()) # we need to know the revision numbers of revisions to determine # the revision numbers of their descendants # this is a graph from node to [revno_tuple, first_child] # where first_child is True if no other children have seen this node # and revno_tuple is the tuple that was assigned to the node. # we dont know revnos to start with, so we start it seeded with # [None, True] self._revnos = dict((revision, [None, True]) for revision in self._graph) # Each mainline revision counts how many child branches have spawned from it. self._revno_to_branch_count = {} # this is a stack storing the depth first search into the graph. self._node_name_stack = [] # at each level of recursion we need the merge depth this node is at: self._node_merge_depth_stack = [] # at each level of 'recursion' we have to check each parent. This # stack stores the parents we have not yet checked for the node at the # matching depth in _node_name_stack self._pending_parents_stack = [] # When we first look at a node we assign it a seqence number from its # leftmost parent. self._first_child_stack = [] # this is a set of the nodes who have been completely analysed for fast # membership checking self._completed_node_names = set() # this is the scheduling of nodes list. # Nodes are scheduled # from the bottom left of the tree: in the tree # A 0 [D, B] # B 1 [C] # C 1 [D] # D 0 [F, E] # E 1 [F] # F 0 # the scheduling order is: F, E, D, C, B, A # that is - 'left subtree, right subtree, node' # which would mean that when we schedule A we can emit the entire tree. self._scheduled_nodes = [] # This records for each node when we have processed its left most # unmerged subtree. After this subtree is scheduled, all other subtrees # have their merge depth increased by one from this nodes merge depth. # it contains tuples - name, merge_depth self._left_subtree_pushed_stack = [] # seed the search with the tip of the branch if (branch_tip is not None and branch_tip != _mod_revision.NULL_REVISION and branch_tip != (_mod_revision.NULL_REVISION,)): parents = self._graph.pop(branch_tip) self._push_node(branch_tip, 0, parents) def sorted(self): """Sort the graph and return as a list. After calling this the sorter is empty and you must create a new one. """ return list(self.iter_topo_order()) def iter_topo_order(self): """Yield the nodes of the graph in a topological order. After finishing iteration the sorter is empty and you cannot continue iteration. """ # These are safe to offload to local variables, because they are used # as a stack and modified in place, never assigned to. node_name_stack = self._node_name_stack node_merge_depth_stack = self._node_merge_depth_stack pending_parents_stack = self._pending_parents_stack left_subtree_pushed_stack = self._left_subtree_pushed_stack completed_node_names = self._completed_node_names scheduled_nodes = self._scheduled_nodes graph_pop = self._graph.pop def push_node(node_name, merge_depth, parents, node_name_stack_append=node_name_stack.append, node_merge_depth_stack_append=node_merge_depth_stack.append, left_subtree_pushed_stack_append=left_subtree_pushed_stack.append, pending_parents_stack_append=pending_parents_stack.append, first_child_stack_append=self._first_child_stack.append, revnos=self._revnos, ): """Add node_name to the pending node stack. Names in this stack will get emitted into the output as they are popped off the stack. This inlines a lot of self._variable.append functions as local variables. """ node_name_stack_append(node_name) node_merge_depth_stack_append(merge_depth) left_subtree_pushed_stack_append(False) pending_parents_stack_append(list(parents)) # as we push it, check if it is the first child parent_info = None if parents: # node has parents, assign from the left most parent. try: parent_info = revnos[parents[0]] except KeyError: # Left-hand parent is a ghost, consider it not to exist pass if parent_info is not None: first_child = parent_info[1] parent_info[1] = False else: # We don't use the same algorithm here, but we need to keep the # stack in line first_child = None first_child_stack_append(first_child) def pop_node(node_name_stack_pop=node_name_stack.pop, node_merge_depth_stack_pop=node_merge_depth_stack.pop, first_child_stack_pop=self._first_child_stack.pop, left_subtree_pushed_stack_pop=left_subtree_pushed_stack.pop, pending_parents_stack_pop=pending_parents_stack.pop, original_graph=self._original_graph, revnos=self._revnos, completed_node_names_add=self._completed_node_names.add, scheduled_nodes_append=scheduled_nodes.append, revno_to_branch_count=self._revno_to_branch_count, ): """Pop the top node off the stack The node is appended to the sorted output. """ # we are returning from the flattened call frame: # pop off the local variables node_name = node_name_stack_pop() merge_depth = node_merge_depth_stack_pop() first_child = first_child_stack_pop() # remove this node from the pending lists: left_subtree_pushed_stack_pop() pending_parents_stack_pop() parents = original_graph[node_name] parent_revno = None if parents: # node has parents, assign from the left most parent. try: parent_revno = revnos[parents[0]][0] except KeyError: # left-hand parent is a ghost, treat it as not existing pass if parent_revno is not None: if not first_child: # not the first child, make a new branch base_revno = parent_revno[0] branch_count = revno_to_branch_count.get(base_revno, 0) branch_count += 1 revno_to_branch_count[base_revno] = branch_count revno = (parent_revno[0], branch_count, 1) # revno = (parent_revno[0], branch_count, parent_revno[-1]+1) else: # as the first child, we just increase the final revision # number revno = parent_revno[:-1] + (parent_revno[-1] + 1,) else: # no parents, use the root sequence root_count = revno_to_branch_count.get(0, -1) root_count += 1 if root_count: revno = (0, root_count, 1) else: revno = (1,) revno_to_branch_count[0] = root_count # store the revno for this node for future reference revnos[node_name][0] = revno completed_node_names_add(node_name) scheduled_nodes_append((node_name, merge_depth, revno)) return node_name while node_name_stack: # loop until this call completes. parents_to_visit = pending_parents_stack[-1] # if all parents are done, the revision is done if not parents_to_visit: # append the revision to the topo sorted scheduled list: # all the nodes parents have been scheduled added, now # we can add it to the output. pop_node() else: while pending_parents_stack[-1]: if not left_subtree_pushed_stack[-1]: # recurse depth first into the primary parent next_node_name = pending_parents_stack[-1].pop(0) is_left_subtree = True left_subtree_pushed_stack[-1] = True else: # place any merges in right-to-left order for scheduling # which gives us left-to-right order after we reverse # the scheduled queue. XXX: This has the effect of # allocating common-new revisions to the right-most # subtree rather than the left most, which will # display nicely (you get smaller trees at the top # of the combined merge). next_node_name = pending_parents_stack[-1].pop() is_left_subtree = False if next_node_name in completed_node_names: # this parent was completed by a child on the # call stack. skip it. continue # otherwise transfer it from the source graph into the # top of the current depth first search stack. try: parents = graph_pop(next_node_name) except KeyError: # if the next node is not in the source graph it has # already been popped from it and placed into the # current search stack (but not completed or we would # have hit the continue 4 lines up. # this indicates a cycle. if next_node_name in self._original_graph: raise errors.GraphCycleError(node_name_stack) else: # This is just a ghost parent, ignore it continue next_merge_depth = 0 if is_left_subtree: # a new child branch from name_stack[-1] next_merge_depth = 0 else: next_merge_depth = 1 next_merge_depth = ( node_merge_depth_stack[-1] + next_merge_depth) push_node( next_node_name, next_merge_depth, parents) # and do not continue processing parents until this 'call' # has recursed. break # We have scheduled the graph. Now deliver the ordered output: sequence_number = 0 stop_revision = self._stop_revision generate_revno = self._generate_revno original_graph = self._original_graph while scheduled_nodes: node_name, merge_depth, revno = scheduled_nodes.pop() if node_name == stop_revision: return if not len(scheduled_nodes): # last revision is the end of a merge end_of_merge = True elif scheduled_nodes[-1][1] < merge_depth: # the next node is to our left end_of_merge = True elif (scheduled_nodes[-1][1] == merge_depth and (scheduled_nodes[-1][0] not in original_graph[node_name])): # the next node was part of a multiple-merge. end_of_merge = True else: end_of_merge = False if generate_revno: yield (sequence_number, node_name, merge_depth, revno, end_of_merge) else: yield (sequence_number, node_name, merge_depth, end_of_merge) sequence_number += 1 def _push_node(self, node_name, merge_depth, parents): """Add node_name to the pending node stack. Names in this stack will get emitted into the output as they are popped off the stack. """ self._node_name_stack.append(node_name) self._node_merge_depth_stack.append(merge_depth) self._left_subtree_pushed_stack.append(False) self._pending_parents_stack.append(list(parents)) # as we push it, figure out if this is the first child parent_info = None if parents: # node has parents, assign from the left most parent. try: parent_info = self._revnos[parents[0]] except KeyError: # Left-hand parent is a ghost, consider it not to exist pass if parent_info is not None: first_child = parent_info[1] parent_info[1] = False else: # We don't use the same algorithm here, but we need to keep the # stack in line first_child = None self._first_child_stack.append(first_child) def _pop_node(self): """Pop the top node off the stack The node is appended to the sorted output. """ # we are returning from the flattened call frame: # pop off the local variables node_name = self._node_name_stack.pop() merge_depth = self._node_merge_depth_stack.pop() first_child = self._first_child_stack.pop() # remove this node from the pending lists: self._left_subtree_pushed_stack.pop() self._pending_parents_stack.pop() parents = self._original_graph[node_name] parent_revno = None if parents: # node has parents, assign from the left most parent. try: parent_revno = self._revnos[parents[0]][0] except KeyError: # left-hand parent is a ghost, treat it as not existing pass if parent_revno is not None: if not first_child: # not the first child, make a new branch base_revno = parent_revno[0] branch_count = self._revno_to_branch_count.get(base_revno, 0) branch_count += 1 self._revno_to_branch_count[base_revno] = branch_count revno = (parent_revno[0], branch_count, 1) # revno = (parent_revno[0], branch_count, parent_revno[-1]+1) else: # as the first child, we just increase the final revision # number revno = parent_revno[:-1] + (parent_revno[-1] + 1,) else: # no parents, use the root sequence root_count = self._revno_to_branch_count.get(0, 0) root_count = self._revno_to_branch_count.get(0, -1) root_count += 1 if root_count: revno = (0, root_count, 1) else: revno = (1,) self._revno_to_branch_count[0] = root_count # store the revno for this node for future reference self._revnos[node_name][0] = revno self._completed_node_names.add(node_name) self._scheduled_nodes.append((node_name, merge_depth, self._revnos[node_name][0])) return node_name