30
35
graph -- sequence of pairs of node->parents_list.
32
The result is a list of node names, such that all parents come before
37
The result is a list of node names, such that all parents come before their
35
40
node identifiers can be any hashable object, and are typically strings.
42
This function has the same purpose as the TopoSorter class, but uses a
43
different algorithm to sort the graph. That means that while both return a
44
list with parents before their child nodes, the exact ordering can be
47
topo_sort is faster when the whole list is needed, while when iterating
48
over a part of the list, TopoSorter.iter_topo_order should be used.
37
return TopoSorter(graph).sorted()
50
kg = _mod_graph.KnownGraph(dict(graph))
40
54
class TopoSorter(object):
42
56
def __init__(self, graph):
43
57
"""Topological sorting of a graph.
45
59
:param graph: sequence of pairs of node_name->parent_names_list.
46
60
i.e. [('C', ['B']), ('B', ['A']), ('A', [])]
47
61
For this input the output from the sort or
48
62
iter_topo_order routines will be:
51
65
node identifiers can be any hashable object, and are typically strings.
53
67
If you have a graph like [('a', ['b']), ('a', ['c'])] this will only use
56
70
The graph is sorted lazily: until you iterate or sort the input is
57
71
not processed other than to create an internal representation.
59
iteration or sorting may raise GraphCycleError if a cycle is present
73
iteration or sorting may raise GraphCycleError if a cycle is present
62
# a dict of the graph.
76
# store a dict of the graph.
63
77
self._graph = dict(graph)
64
self._visitable = set(self._graph)
66
# self._original_graph = dict(graph)
68
# this is a stack storing the depth first search into the graph.
69
self._node_name_stack = []
70
# at each level of 'recursion' we have to check each parent. This
71
# stack stores the parents we have not yet checked for the node at the
72
# matching depth in _node_name_stack
73
self._pending_parents_stack = []
74
# this is a set of the completed nodes for fast checking whether a
75
# parent in a node we are processing on the stack has already been
76
# emitted and thus can be skipped.
77
self._completed_node_names = set()
80
80
"""Sort the graph and return as a list.
82
82
After calling this the sorter is empty and you must create a new one.
84
84
return list(self.iter_topo_order())
96
96
def iter_topo_order(self):
97
97
"""Yield the nodes of the graph in a topological order.
99
99
After finishing iteration the sorter is empty and you cannot continue
103
visitable = set(graph)
105
# this is a stack storing the depth first search into the graph.
106
pending_node_stack = []
107
# at each level of 'recursion' we have to check each parent. This
108
# stack stores the parents we have not yet checked for the node at the
109
# matching depth in pending_node_stack
110
pending_parents_stack = []
112
# this is a set of the completed nodes for fast checking whether a
113
# parent in a node we are processing on the stack has already been
114
# emitted and thus can be skipped.
115
completed_node_names = set()
103
118
# now pick a random node in the source graph, and transfer it to the
104
# top of the depth first search stack.
105
node_name, parents = self._graph.popitem()
106
self._push_node(node_name, parents)
107
while self._node_name_stack:
108
# loop until this call completes.
109
parents_to_visit = self._pending_parents_stack[-1]
110
# if all parents are done, the revision is done
119
# top of the depth first search stack of pending nodes.
120
node_name, parents = graph.popitem()
121
pending_node_stack.append(node_name)
122
pending_parents_stack.append(list(parents))
124
# loop until pending_node_stack is empty
125
while pending_node_stack:
126
parents_to_visit = pending_parents_stack[-1]
127
# if there are no parents left, the revision is done
111
128
if not parents_to_visit:
112
129
# append the revision to the topo sorted list
113
# all the nodes parents have been added to the output, now
114
# we can add it to the output.
115
yield self._pop_node()
130
# all the nodes parents have been added to the output,
131
# now we can add it to the output.
132
popped_node = pending_node_stack.pop()
133
pending_parents_stack.pop()
134
completed_node_names.add(popped_node)
117
while self._pending_parents_stack[-1]:
118
# recurse depth first into a single parent
119
next_node_name = self._pending_parents_stack[-1].pop()
120
if next_node_name in self._completed_node_names:
121
# this parent was completed by a child on the
122
# call stack. skip it.
124
if next_node_name not in self._visitable:
126
# otherwise transfer it from the source graph into the
127
# top of the current depth first search stack.
129
parents = self._graph.pop(next_node_name)
131
# if the next node is not in the source graph it has
132
# already been popped from it and placed into the
133
# current search stack (but not completed or we would
134
# have hit the continue 4 lines up.
135
# this indicates a cycle.
136
raise errors.GraphCycleError(self._node_name_stack)
137
self._push_node(next_node_name, parents)
138
# and do not continue processing parents until this 'call'
142
def _push_node(self, node_name, parents):
143
"""Add node_name to the pending node stack.
145
Names in this stack will get emitted into the output as they are popped
148
self._node_name_stack.append(node_name)
149
self._pending_parents_stack.append(list(parents))
152
"""Pop the top node off the stack
154
The node is appended to the sorted output.
156
# we are returning from the flattened call frame:
157
# pop off the local variables
158
node_name = self._node_name_stack.pop()
159
self._pending_parents_stack.pop()
161
self._completed_node_names.add(node_name)
137
# recurse depth first into a single parent
138
next_node_name = parents_to_visit.pop()
140
if next_node_name in completed_node_names:
141
# parent was already completed by a child, skip it.
143
if next_node_name not in visitable:
144
# parent is not a node in the original graph, skip it.
147
# transfer it along with its parents from the source graph
148
# into the top of the current depth first search stack.
150
parents = graph.pop(next_node_name)
152
# if the next node is not in the source graph it has
153
# already been popped from it and placed into the
154
# current search stack (but not completed or we would
155
# have hit the continue 6 lines up). this indicates a
157
raise errors.GraphCycleError(pending_node_stack)
158
pending_node_stack.append(next_node_name)
159
pending_parents_stack.append(list(parents))
165
162
def merge_sort(graph, branch_tip, mainline_revisions=None, generate_revno=False):
166
163
"""Topological sort a graph which groups merges.
168
165
:param graph: sequence of pairs of node->parents_list.
169
:param branch_tip: the tip of the branch to graph. Revisions not
166
:param branch_tip: the tip of the branch to graph. Revisions not
170
167
reachable from branch_tip are not included in the
172
169
:param mainline_revisions: If not None this forces a mainline to be
232
230
The result is a list sorted so that all parents come before
233
231
their children. Each element of the list is a tuple containing:
234
232
(sequence_number, node_name, merge_depth, end_of_merge)
235
* sequence_number: The sequence of this row in the output. Useful for
233
* sequence_number: The sequence of this row in the output. Useful for
237
235
* node_name: The node name: opaque text to the merge routine.
238
236
* merge_depth: How many levels of merging deep this node has been
240
238
* revno_sequence: When requested this field provides a sequence of
241
239
revision numbers for all revisions. The format is:
242
REVNO[[.BRANCHREVNO.REVNO] ...]. BRANCHREVNO is the number of the
240
(REVNO, BRANCHNUM, BRANCHREVNO). BRANCHNUM is the number of the
243
241
branch that the revno is on. From left to right the REVNO numbers
244
242
are the sequence numbers within that branch of the revision.
245
243
For instance, the graph {A:[], B:['A'], C:['A', 'B']} will get
285
283
C is the end of a cluster due to rule 1.
286
D is not the end of a cluster from rule 1, but is from rule 2: E
284
D is not the end of a cluster from rule 1, but is from rule 2: E
287
285
is not its left most ancestor
288
286
E is the end of a cluster due to rule 1
289
287
F might be but we need more data.
291
289
we show connecting lines to a parent when:
292
290
- The parent is the start of a merge within this cluster.
293
That is, the merge was not done to the mainline before this cluster
291
That is, the merge was not done to the mainline before this cluster
294
292
was merged to the mainline.
295
293
This can be detected thus:
296
* The parent has a higher merge depth and is the next revision in
294
* The parent has a higher merge depth and is the next revision in
299
297
The next revision in the list constraint is needed for this case:
301
B 1 [C, F] # we do not want to show a line to F which is depth 2
299
B 1 [C, F] # we do not want to show a line to F which is depth 2
303
C 1 [H] # note that this is a long line to show back to the
301
C 1 [H] # note that this is a long line to show back to the
304
302
ancestor - see the end of merge rules.
362
366
self._original_graph = dict(self._graph.items())
363
367
# we need to know the revision numbers of revisions to determine
364
368
# the revision numbers of their descendants
365
# this is a graph from node to [revno_tuple, sequence_number]
366
# where sequence is the number of branches made from the node,
369
# this is a graph from node to [revno_tuple, first_child]
370
# where first_child is True if no other children have seen this node
367
371
# and revno_tuple is the tuple that was assigned to the node.
368
372
# we dont know revnos to start with, so we start it seeded with
370
self._revnos = dict((revision, [None, 0]) for revision in self._graph)
371
# the global implicit root node has revno 0, but we need to know
372
# the sequence number for it too:
373
self._root_sequence = 0
374
self._revnos = dict((revision, [None, True])
375
for revision in self._graph)
376
# Each mainline revision counts how many child branches have spawned from it.
377
self._revno_to_branch_count = {}
375
379
# this is a stack storing the depth first search into the graph.
376
380
self._node_name_stack = []
377
381
# at each level of recursion we need the merge depth this node is at:
378
382
self._node_merge_depth_stack = []
379
383
# at each level of 'recursion' we have to check each parent. This
380
# stack stores the parents we have not yet checked for the node at the
384
# stack stores the parents we have not yet checked for the node at the
381
385
# matching depth in _node_name_stack
382
386
self._pending_parents_stack = []
383
387
# When we first look at a node we assign it a seqence number from its
384
388
# leftmost parent.
385
self._assigned_sequence_stack = []
389
self._first_child_stack = []
386
390
# this is a set of the nodes who have been completely analysed for fast
387
391
# membership checking
388
392
self._completed_node_names = set()
398
# the scheduling order is: F, E, D, C, B, A
402
# the scheduling order is: F, E, D, C, B, A
399
403
# that is - 'left subtree, right subtree, node'
400
404
# which would mean that when we schedule A we can emit the entire tree.
401
405
self._scheduled_nodes = []
402
# This records for each node when we have processed its left most
406
# This records for each node when we have processed its left most
403
407
# unmerged subtree. After this subtree is scheduled, all other subtrees
404
408
# have their merge depth increased by one from this nodes merge depth.
405
409
# it contains tuples - name, merge_depth
406
410
self._left_subtree_pushed_stack = []
408
412
# seed the search with the tip of the branch
409
if branch_tip is not None:
413
if (branch_tip is not None and
414
branch_tip != _mod_revision.NULL_REVISION and
415
branch_tip != (_mod_revision.NULL_REVISION,)):
410
416
parents = self._graph.pop(branch_tip)
411
417
self._push_node(branch_tip, 0, parents)
413
419
def sorted(self):
414
420
"""Sort the graph and return as a list.
416
422
After calling this the sorter is empty and you must create a new one.
418
424
return list(self.iter_topo_order())
420
426
def iter_topo_order(self):
421
427
"""Yield the nodes of the graph in a topological order.
423
429
After finishing iteration the sorter is empty and you cannot continue
455
460
node_merge_depth_stack_append(merge_depth)
456
461
left_subtree_pushed_stack_append(False)
457
462
pending_parents_stack_append(list(parents))
458
# as we push it, assign it a sequence number against its parent:
459
parents = original_graph[node_name]
463
# as we push it, check if it is the first child
461
466
# node has parents, assign from the left most parent.
462
parent_revno = revnos[parents[0]]
463
sequence = parent_revno[1]
468
parent_info = revnos[parents[0]]
470
# Left-hand parent is a ghost, consider it not to exist
472
if parent_info is not None:
473
first_child = parent_info[1]
474
parent_info[1] = False
466
# no parents, use the root sequence
467
sequence = self._root_sequence
468
self._root_sequence +=1
469
assigned_sequence_stack_append(sequence)
476
# We don't use the same algorithm here, but we need to keep the
479
first_child_stack_append(first_child)
471
481
def pop_node(node_name_stack_pop=node_name_stack.pop,
472
482
node_merge_depth_stack_pop=node_merge_depth_stack.pop,
473
assigned_sequence_stack_pop=self._assigned_sequence_stack.pop,
483
first_child_stack_pop=self._first_child_stack.pop,
474
484
left_subtree_pushed_stack_pop=left_subtree_pushed_stack.pop,
475
485
pending_parents_stack_pop=pending_parents_stack.pop,
476
486
original_graph=self._original_graph,
477
487
revnos=self._revnos,
478
488
completed_node_names_add=self._completed_node_names.add,
479
489
scheduled_nodes_append=scheduled_nodes.append,
490
revno_to_branch_count=self._revno_to_branch_count,
481
492
"""Pop the top node off the stack
486
497
# pop off the local variables
487
498
node_name = node_name_stack_pop()
488
499
merge_depth = node_merge_depth_stack_pop()
489
sequence = assigned_sequence_stack_pop()
500
first_child = first_child_stack_pop()
490
501
# remove this node from the pending lists:
491
502
left_subtree_pushed_stack_pop()
492
503
pending_parents_stack_pop()
494
505
parents = original_graph[node_name]
496
508
# node has parents, assign from the left most parent.
497
parent_revno = revnos[parents[0]]
510
parent_revno = revnos[parents[0]][0]
512
# left-hand parent is a ghost, treat it as not existing
514
if parent_revno is not None:
499
516
# not the first child, make a new branch
500
revno = parent_revno[0] + (sequence, 1)
517
base_revno = parent_revno[0]
518
branch_count = revno_to_branch_count.get(base_revno, 0)
520
revno_to_branch_count[base_revno] = branch_count
521
revno = (parent_revno[0], branch_count, 1)
522
# revno = (parent_revno[0], branch_count, parent_revno[-1]+1)
502
# increment the sequence number within the branch
503
revno = parent_revno[0][:-1] + (parent_revno[0][-1] + 1,)
524
# as the first child, we just increase the final revision
526
revno = parent_revno[:-1] + (parent_revno[-1] + 1,)
505
528
# no parents, use the root sequence
507
# make a parallel import revision number
508
revno = (0, sequence, 1)
529
root_count = revno_to_branch_count.get(0, -1)
532
revno = (0, root_count, 1)
535
revno_to_branch_count[0] = root_count
512
537
# store the revno for this node for future reference
513
538
revnos[node_name][0] = revno
530
555
if not left_subtree_pushed_stack[-1]:
531
556
# recurse depth first into the primary parent
532
557
next_node_name = pending_parents_stack[-1].pop(0)
558
is_left_subtree = True
559
left_subtree_pushed_stack[-1] = True
534
561
# place any merges in right-to-left order for scheduling
535
562
# which gives us left-to-right order after we reverse
536
# the scheduled queue. XXX: This has the effect of
563
# the scheduled queue. XXX: This has the effect of
537
564
# allocating common-new revisions to the right-most
538
# subtree rather than the left most, which will
565
# subtree rather than the left most, which will
539
566
# display nicely (you get smaller trees at the top
540
567
# of the combined merge).
541
568
next_node_name = pending_parents_stack[-1].pop()
569
is_left_subtree = False
542
570
if next_node_name in completed_node_names:
543
571
# this parent was completed by a child on the
544
572
# call stack. skip it.
610
641
self._node_merge_depth_stack.append(merge_depth)
611
642
self._left_subtree_pushed_stack.append(False)
612
643
self._pending_parents_stack.append(list(parents))
613
# as we push it, assign it a sequence number against its parent:
614
parents = self._original_graph[node_name]
644
# as we push it, figure out if this is the first child
616
647
# node has parents, assign from the left most parent.
617
parent_revno = self._revnos[parents[0]]
618
sequence = parent_revno[1]
649
parent_info = self._revnos[parents[0]]
651
# Left-hand parent is a ghost, consider it not to exist
653
if parent_info is not None:
654
first_child = parent_info[1]
655
parent_info[1] = False
621
# no parents, use the root sequence
622
sequence = self._root_sequence
623
self._root_sequence +=1
624
self._assigned_sequence_stack.append(sequence)
657
# We don't use the same algorithm here, but we need to keep the
660
self._first_child_stack.append(first_child)
626
662
def _pop_node(self):
627
"""Pop the top node off the stack
663
"""Pop the top node off the stack
629
665
The node is appended to the sorted output.
632
668
# pop off the local variables
633
669
node_name = self._node_name_stack.pop()
634
670
merge_depth = self._node_merge_depth_stack.pop()
635
sequence = self._assigned_sequence_stack.pop()
671
first_child = self._first_child_stack.pop()
636
672
# remove this node from the pending lists:
637
673
self._left_subtree_pushed_stack.pop()
638
674
self._pending_parents_stack.pop()
640
676
parents = self._original_graph[node_name]
642
679
# node has parents, assign from the left most parent.
643
parent_revno = self._revnos[parents[0]]
681
parent_revno = self._revnos[parents[0]][0]
683
# left-hand parent is a ghost, treat it as not existing
685
if parent_revno is not None:
645
687
# not the first child, make a new branch
646
revno = parent_revno[0] + (sequence, 1)
688
base_revno = parent_revno[0]
689
branch_count = self._revno_to_branch_count.get(base_revno, 0)
691
self._revno_to_branch_count[base_revno] = branch_count
692
revno = (parent_revno[0], branch_count, 1)
693
# revno = (parent_revno[0], branch_count, parent_revno[-1]+1)
648
# increment the sequence number within the branch
649
revno = parent_revno[0][:-1] + (parent_revno[0][-1] + 1,)
695
# as the first child, we just increase the final revision
697
revno = parent_revno[:-1] + (parent_revno[-1] + 1,)
651
699
# no parents, use the root sequence
653
# make a parallel import revision number
654
revno = (0, sequence, 1)
700
root_count = self._revno_to_branch_count.get(0, 0)
701
root_count = self._revno_to_branch_count.get(0, -1)
704
revno = (0, root_count, 1)
707
self._revno_to_branch_count[0] = root_count
658
709
# store the revno for this node for future reference
659
710
self._revnos[node_name][0] = revno
added
removed
bzrlib/tsort.py
