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31
graph -- sequence of pairs of node->parents_list.
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The result is a list of node names, such that all parents come before their
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The result is a list of node names, such that all parents come before
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36
node identifiers can be any hashable object, and are typically strings.
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This function has the same purpose as the TopoSorter class, but uses a
42
different algorithm to sort the graph. That means that while both return a
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list with parents before their child nodes, the exact ordering can be
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topo_sort is faster when the whole list is needed, while when iterating
47
over a part of the list, TopoSorter.iter_topo_order should be used.
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kg = _mod_graph.KnownGraph(dict(graph))
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return TopoSorter(graph).sorted()
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41
class TopoSorter(object):
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43
def __init__(self, graph):
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"""Topological sorting of a graph.
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46
:param graph: sequence of pairs of node_name->parent_names_list.
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47
i.e. [('C', ['B']), ('B', ['A']), ('A', [])]
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For this input the output from the sort or
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49
iter_topo_order routines will be:
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52
node identifiers can be any hashable object, and are typically strings.
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54
If you have a graph like [('a', ['b']), ('a', ['c'])] this will only use
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57
The graph is sorted lazily: until you iterate or sort the input is
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not processed other than to create an internal representation.
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iteration or sorting may raise GraphCycleError if a cycle is present
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iteration or sorting may raise GraphCycleError if a cycle is present
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# store a dict of the graph.
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# a dict of the graph.
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self._graph = dict(graph)
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self._visitable = set(self._graph)
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# self._original_graph = dict(graph)
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# this is a stack storing the depth first search into the graph.
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self._node_name_stack = []
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# at each level of 'recursion' we have to check each parent. This
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# stack stores the parents we have not yet checked for the node at the
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# matching depth in _node_name_stack
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self._pending_parents_stack = []
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# this is a set of the completed nodes for fast checking whether a
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# parent in a node we are processing on the stack has already been
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# emitted and thus can be skipped.
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self._completed_node_names = set()
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"""Sort the graph and return as a list.
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After calling this the sorter is empty and you must create a new one.
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return list(self.iter_topo_order())
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def iter_topo_order(self):
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"""Yield the nodes of the graph in a topological order.
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After finishing iteration the sorter is empty and you cannot continue
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visitable = set(graph)
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# this is a stack storing the depth first search into the graph.
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pending_node_stack = []
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# at each level of 'recursion' we have to check each parent. This
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# stack stores the parents we have not yet checked for the node at the
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# matching depth in pending_node_stack
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pending_parents_stack = []
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# this is a set of the completed nodes for fast checking whether a
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# parent in a node we are processing on the stack has already been
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# emitted and thus can be skipped.
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completed_node_names = set()
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104
# now pick a random node in the source graph, and transfer it to the
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# top of the depth first search stack of pending nodes.
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node_name, parents = graph.popitem()
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pending_node_stack.append(node_name)
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pending_parents_stack.append(list(parents))
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# loop until pending_node_stack is empty
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while pending_node_stack:
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parents_to_visit = pending_parents_stack[-1]
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# if there are no parents left, the revision is done
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# top of the depth first search stack.
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node_name, parents = self._graph.popitem()
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self._push_node(node_name, parents)
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while self._node_name_stack:
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# loop until this call completes.
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parents_to_visit = self._pending_parents_stack[-1]
111
# if all parents are done, the revision is done
127
112
if not parents_to_visit:
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# append the revision to the topo sorted list
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# all the nodes parents have been added to the output,
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# now we can add it to the output.
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popped_node = pending_node_stack.pop()
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pending_parents_stack.pop()
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completed_node_names.add(popped_node)
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# all the nodes parents have been added to the output, now
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# we can add it to the output.
116
yield self._pop_node()
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# recurse depth first into a single parent
137
next_node_name = parents_to_visit.pop()
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if next_node_name in completed_node_names:
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# parent was already completed by a child, skip it.
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if next_node_name not in visitable:
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# parent is not a node in the original graph, skip it.
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# transfer it along with its parents from the source graph
147
# into the top of the current depth first search stack.
149
parents = graph.pop(next_node_name)
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# if the next node is not in the source graph it has
152
# already been popped from it and placed into the
153
# current search stack (but not completed or we would
154
# have hit the continue 6 lines up). this indicates a
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raise errors.GraphCycleError(pending_node_stack)
157
pending_node_stack.append(next_node_name)
158
pending_parents_stack.append(list(parents))
118
while self._pending_parents_stack[-1]:
119
# recurse depth first into a single parent
120
next_node_name = self._pending_parents_stack[-1].pop()
121
if next_node_name in self._completed_node_names:
122
# this parent was completed by a child on the
123
# call stack. skip it.
125
if next_node_name not in self._visitable:
127
# otherwise transfer it from the source graph into the
128
# top of the current depth first search stack.
130
parents = self._graph.pop(next_node_name)
132
# if the next node is not in the source graph it has
133
# already been popped from it and placed into the
134
# current search stack (but not completed or we would
135
# have hit the continue 4 lines up.
136
# this indicates a cycle.
137
raise errors.GraphCycleError(self._node_name_stack)
138
self._push_node(next_node_name, parents)
139
# and do not continue processing parents until this 'call'
143
def _push_node(self, node_name, parents):
144
"""Add node_name to the pending node stack.
146
Names in this stack will get emitted into the output as they are popped
149
self._node_name_stack.append(node_name)
150
self._pending_parents_stack.append(list(parents))
153
"""Pop the top node off the stack
155
The node is appended to the sorted output.
157
# we are returning from the flattened call frame:
158
# pop off the local variables
159
node_name = self._node_name_stack.pop()
160
self._pending_parents_stack.pop()
162
self._completed_node_names.add(node_name)
161
166
def merge_sort(graph, branch_tip, mainline_revisions=None, generate_revno=False):
162
167
"""Topological sort a graph which groups merges.
164
169
:param graph: sequence of pairs of node->parents_list.
165
:param branch_tip: the tip of the branch to graph. Revisions not
170
:param branch_tip: the tip of the branch to graph. Revisions not
166
171
reachable from branch_tip are not included in the
168
173
:param mainline_revisions: If not None this forces a mainline to be
281
286
C is the end of a cluster due to rule 1.
282
D is not the end of a cluster from rule 1, but is from rule 2: E
287
D is not the end of a cluster from rule 1, but is from rule 2: E
283
288
is not its left most ancestor
284
289
E is the end of a cluster due to rule 1
285
290
F might be but we need more data.
287
292
we show connecting lines to a parent when:
288
293
- The parent is the start of a merge within this cluster.
289
That is, the merge was not done to the mainline before this cluster
294
That is, the merge was not done to the mainline before this cluster
290
295
was merged to the mainline.
291
296
This can be detected thus:
292
* The parent has a higher merge depth and is the next revision in
297
* The parent has a higher merge depth and is the next revision in
295
300
The next revision in the list constraint is needed for this case:
297
B 1 [C, F] # we do not want to show a line to F which is depth 2
302
B 1 [C, F] # we do not want to show a line to F which is depth 2
299
C 1 [H] # note that this is a long line to show back to the
304
C 1 [H] # note that this is a long line to show back to the
300
305
ancestor - see the end of merge rules.
400
# the scheduling order is: F, E, D, C, B, A
399
# the scheduling order is: F, E, D, C, B, A
401
400
# that is - 'left subtree, right subtree, node'
402
401
# which would mean that when we schedule A we can emit the entire tree.
403
402
self._scheduled_nodes = []
404
# This records for each node when we have processed its left most
403
# This records for each node when we have processed its left most
405
404
# unmerged subtree. After this subtree is scheduled, all other subtrees
406
405
# have their merge depth increased by one from this nodes merge depth.
407
406
# it contains tuples - name, merge_depth
553
539
if not left_subtree_pushed_stack[-1]:
554
540
# recurse depth first into the primary parent
555
541
next_node_name = pending_parents_stack[-1].pop(0)
556
is_left_subtree = True
557
left_subtree_pushed_stack[-1] = True
559
543
# place any merges in right-to-left order for scheduling
560
544
# which gives us left-to-right order after we reverse
561
# the scheduled queue. XXX: This has the effect of
545
# the scheduled queue. XXX: This has the effect of
562
546
# allocating common-new revisions to the right-most
563
# subtree rather than the left most, which will
547
# subtree rather than the left most, which will
564
548
# display nicely (you get smaller trees at the top
565
549
# of the combined merge).
566
550
next_node_name = pending_parents_stack[-1].pop()
567
is_left_subtree = False
568
551
if next_node_name in completed_node_names:
569
552
# this parent was completed by a child on the
570
553
# call stack. skip it.