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# Revision graph generator for Mercurial
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#
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# Copyright 2008 Dirkjan Ochtman <dirkjan@ochtman.nl>
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# Copyright 2007 Joel Rosdahl <joel@rosdahl.net>
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#
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# This software may be used and distributed according to the terms of the
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# GNU General Public License version 2 or any later version.
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"""supports walking the history as DAGs suitable for graphical output
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The most basic format we use is that of::
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(id, type, data, [parentids])
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The node and parent ids are arbitrary integers which identify a node in the
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context of the graph returned. Type is a constant specifying the node type.
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Data depends on type.
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"""
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from __future__ import absolute_import
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import heapq
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from .node import nullrev
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from . import (
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revset,
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util,
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)
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CHANGESET = 'C'
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def groupbranchiter(revs, parentsfunc, firstbranch=()):
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"""Yield revisions from heads to roots one (topo) branch at a time.
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This function aims to be used by a graph generator that wishes to minimize
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the number of parallel branches and their interleaving.
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Example iteration order (numbers show the "true" order in a changelog):
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o 4
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o 1
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| o 3
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| o 2
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|/
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o 0
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Note that the ancestors of merges are understood by the current
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algorithm to be on the same branch. This means no reordering will
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occur behind a merge.
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"""
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### Quick summary of the algorithm
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#
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# This function is based around a "retention" principle. We keep revisions
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# in memory until we are ready to emit a whole branch that immediately
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# "merges" into an existing one. This reduces the number of parallel
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# branches with interleaved revisions.
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#
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# During iteration revs are split into two groups:
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# A) revision already emitted
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# B) revision in "retention". They are stored as different subgroups.
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#
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# for each REV, we do the following logic:
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#
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# 1) if REV is a parent of (A), we will emit it. If there is a
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# retention group ((B) above) that is blocked on REV being
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# available, we emit all the revisions out of that retention
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# group first.
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#
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# 2) else, we'll search for a subgroup in (B) awaiting for REV to be
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# available, if such subgroup exist, we add REV to it and the subgroup is
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# now awaiting for REV.parents() to be available.
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#
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# 3) finally if no such group existed in (B), we create a new subgroup.
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#
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#
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# To bootstrap the algorithm, we emit the tipmost revision (which
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# puts it in group (A) from above).
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revs.sort(reverse=True)
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# Set of parents of revision that have been emitted. They can be considered
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# unblocked as the graph generator is already aware of them so there is no
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# need to delay the revisions that reference them.
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#
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# If someone wants to prioritize a branch over the others, pre-filling this
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# set will force all other branches to wait until this branch is ready to be
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# emitted.
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unblocked = set(firstbranch)
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# list of groups waiting to be displayed, each group is defined by:
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#
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# (revs: lists of revs waiting to be displayed,
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# blocked: set of that cannot be displayed before those in 'revs')
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#
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# The second value ('blocked') correspond to parents of any revision in the
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# group ('revs') that is not itself contained in the group. The main idea
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# of this algorithm is to delay as much as possible the emission of any
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# revision. This means waiting for the moment we are about to display
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# these parents to display the revs in a group.
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#
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# This first implementation is smart until it encounters a merge: it will
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# emit revs as soon as any parent is about to be emitted and can grow an
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# arbitrary number of revs in 'blocked'. In practice this mean we properly
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# retains new branches but gives up on any special ordering for ancestors
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# of merges. The implementation can be improved to handle this better.
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#
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# The first subgroup is special. It corresponds to all the revision that
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# were already emitted. The 'revs' lists is expected to be empty and the
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# 'blocked' set contains the parents revisions of already emitted revision.
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#
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# You could pre-seed the <parents> set of groups[0] to a specific
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# changesets to select what the first emitted branch should be.
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groups = [([], unblocked)]
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pendingheap = []
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pendingset = set()
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heapq.heapify(pendingheap)
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heappop = heapq.heappop
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heappush = heapq.heappush
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for currentrev in revs:
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# Heap works with smallest element, we want highest so we invert
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if currentrev not in pendingset:
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heappush(pendingheap, -currentrev)
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pendingset.add(currentrev)
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# iterates on pending rev until after the current rev have been
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# processed.
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rev = None
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while rev != currentrev:
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rev = -heappop(pendingheap)
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pendingset.remove(rev)
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# Seek for a subgroup blocked, waiting for the current revision.
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matching = [i for i, g in enumerate(groups) if rev in g[1]]
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if matching:
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# The main idea is to gather together all sets that are blocked
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# on the same revision.
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#
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# Groups are merged when a common blocking ancestor is
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# observed. For example, given two groups:
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#
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# revs [5, 4] waiting for 1
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# revs [3, 2] waiting for 1
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#
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# These two groups will be merged when we process
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# 1. In theory, we could have merged the groups when
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# we added 2 to the group it is now in (we could have
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# noticed the groups were both blocked on 1 then), but
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# the way it works now makes the algorithm simpler.
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#
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# We also always keep the oldest subgroup first. We can
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# probably improve the behavior by having the longest set
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# first. That way, graph algorithms could minimise the length
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# of parallel lines their drawing. This is currently not done.
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targetidx = matching.pop(0)
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trevs, tparents = groups[targetidx]
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for i in matching:
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gr = groups[i]
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trevs.extend(gr[0])
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tparents |= gr[1]
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# delete all merged subgroups (except the one we kept)
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# (starting from the last subgroup for performance and
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# sanity reasons)
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for i in reversed(matching):
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del groups[i]
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else:
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# This is a new head. We create a new subgroup for it.
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targetidx = len(groups)
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groups.append(([], set([rev])))
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gr = groups[targetidx]
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# We now add the current nodes to this subgroups. This is done
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# after the subgroup merging because all elements from a subgroup
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# that relied on this rev must precede it.
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#
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# we also update the <parents> set to include the parents of the
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# new nodes.
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if rev == currentrev: # only display stuff in rev
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gr[0].append(rev)
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gr[1].remove(rev)
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parents = [p for p in parentsfunc(rev) if p > nullrev]
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gr[1].update(parents)
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for p in parents:
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if p not in pendingset:
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pendingset.add(p)
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heappush(pendingheap, -p)
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# Look for a subgroup to display
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#
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# When unblocked is empty (if clause), we were not waiting for any
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# revisions during the first iteration (if no priority was given) or
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# if we emitted a whole disconnected set of the graph (reached a
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# root). In that case we arbitrarily take the oldest known
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# subgroup. The heuristic could probably be better.
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#
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# Otherwise (elif clause) if the subgroup is blocked on
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# a revision we just emitted, we can safely emit it as
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# well.
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if not unblocked:
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if len(groups) > 1: # display other subset
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targetidx = 1
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gr = groups[1]
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elif not gr[1] & unblocked:
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gr = None
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if gr is not None:
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# update the set of awaited revisions with the one from the
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# subgroup
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unblocked |= gr[1]
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# output all revisions in the subgroup
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for r in gr[0]:
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yield r
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# delete the subgroup that you just output
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# unless it is groups[0] in which case you just empty it.
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if targetidx:
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del groups[targetidx]
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else:
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gr[0][:] = []
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# Check if we have some subgroup waiting for revisions we are not going to
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# iterate over
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for g in groups:
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for r in g[0]:
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yield r
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def dagwalker(repo, revs):
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"""cset DAG generator yielding (id, CHANGESET, ctx, [parentids]) tuples
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This generator function walks through revisions (which should be ordered
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from bigger to lower). It returns a tuple for each node. The node and parent
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ids are arbitrary integers which identify a node in the context of the graph
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returned.
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"""
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if not revs:
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return
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gpcache = {}
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if repo.ui.configbool('experimental', 'graph-group-branches', False):
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firstbranch = ()
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firstbranchrevset = repo.ui.config(
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'experimental', 'graph-group-branches.firstbranch', '')
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if firstbranchrevset:
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firstbranch = repo.revs(firstbranchrevset)
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parentrevs = repo.changelog.parentrevs
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revs = groupbranchiter(revs, parentrevs, firstbranch)
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revs = revset.baseset(revs)
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for rev in revs:
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ctx = repo[rev]
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parents = sorted(set([p.rev() for p in ctx.parents()
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if p.rev() in revs]))
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mpars = [p.rev() for p in ctx.parents() if
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p.rev() != nullrev and p.rev() not in parents]
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for mpar in mpars:
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gp = gpcache.get(mpar)
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if gp is None:
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# precompute slow query as we know reachableroots() goes
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# through all revs (issue4782)
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if not isinstance(revs, revset.baseset):
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revs = revset.baseset(revs)
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gp = gpcache[mpar] = revset.reachableroots(repo, revs, [mpar])
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if not gp:
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parents.append(mpar)
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else:
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parents.extend(g for g in gp if g not in parents)
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yield (ctx.rev(), CHANGESET, ctx, parents)
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def nodes(repo, nodes):
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"""cset DAG generator yielding (id, CHANGESET, ctx, [parentids]) tuples
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This generator function walks the given nodes. It only returns parents
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that are in nodes, too.
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"""
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include = set(nodes)
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for node in nodes:
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ctx = repo[node]
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parents = set([p.rev() for p in ctx.parents() if p.node() in include])
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yield (ctx.rev(), CHANGESET, ctx, sorted(parents))
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def colored(dag, repo):
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"""annotates a DAG with colored edge information
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For each DAG node this function emits tuples::
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(id, type, data, (col, color), [(col, nextcol, color)])
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with the following new elements:
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- Tuple (col, color) with column and color index for the current node
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- A list of tuples indicating the edges between the current node and its
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parents.
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"""
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seen = []
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colors = {}
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newcolor = 1
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config = {}
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for key, val in repo.ui.configitems('graph'):
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if '.' in key:
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branch, setting = key.rsplit('.', 1)
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# Validation
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if setting == "width" and val.isdigit():
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config.setdefault(branch, {})[setting] = int(val)
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elif setting == "color" and val.isalnum():
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config.setdefault(branch, {})[setting] = val
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if config:
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getconf = util.lrucachefunc(
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lambda rev: config.get(repo[rev].branch(), {}))
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else:
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getconf = lambda rev: {}
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for (cur, type, data, parents) in dag:
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# Compute seen and next
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if cur not in seen:
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seen.append(cur) # new head
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colors[cur] = newcolor
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newcolor += 1
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col = seen.index(cur)
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color = colors.pop(cur)
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next = seen[:]
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# Add parents to next
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addparents = [p for p in parents if p not in next]
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next[col:col + 1] = addparents
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# Set colors for the parents
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for i, p in enumerate(addparents):
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if not i:
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colors[p] = color
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else:
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colors[p] = newcolor
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newcolor += 1
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# Add edges to the graph
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edges = []
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for ecol, eid in enumerate(seen):
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if eid in next:
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bconf = getconf(eid)
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edges.append((
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ecol, next.index(eid), colors[eid],
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bconf.get('width', -1),
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bconf.get('color', '')))
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elif eid == cur:
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for p in parents:
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bconf = getconf(p)
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edges.append((
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ecol, next.index(p), color,
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bconf.get('width', -1),
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bconf.get('color', '')))
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# Yield and move on
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yield (cur, type, data, (col, color), edges)
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seen = next
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def asciiedges(type, char, lines, seen, rev, parents):
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"""adds edge info to changelog DAG walk suitable for ascii()"""
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if rev not in seen:
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seen.append(rev)
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nodeidx = seen.index(rev)
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knownparents = []
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newparents = []
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for parent in parents:
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if parent in seen:
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knownparents.append(parent)
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else:
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newparents.append(parent)
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ncols = len(seen)
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nextseen = seen[:]
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nextseen[nodeidx:nodeidx + 1] = newparents
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edges = [(nodeidx, nextseen.index(p)) for p in knownparents if p != nullrev]
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while len(newparents) > 2:
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# ascii() only knows how to add or remove a single column between two
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# calls. Nodes with more than two parents break this constraint so we
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# introduce intermediate expansion lines to grow the active node list
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# slowly.
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edges.append((nodeidx, nodeidx))
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edges.append((nodeidx, nodeidx + 1))
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nmorecols = 1
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yield (type, char, lines, (nodeidx, edges, ncols, nmorecols))
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char = '\\'
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lines = []
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nodeidx += 1
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ncols += 1
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edges = []
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del newparents[0]
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if len(newparents) > 0:
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edges.append((nodeidx, nodeidx))
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if len(newparents) > 1:
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edges.append((nodeidx, nodeidx + 1))
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nmorecols = len(nextseen) - ncols
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seen[:] = nextseen
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yield (type, char, lines, (nodeidx, edges, ncols, nmorecols))
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def _fixlongrightedges(edges):
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for (i, (start, end)) in enumerate(edges):
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if end > start:
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edges[i] = (start, end + 1)
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def _getnodelineedgestail(
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node_index, p_node_index, n_columns, n_columns_diff, p_diff, fix_tail):
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if fix_tail and n_columns_diff == p_diff and n_columns_diff != 0:
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# Still going in the same non-vertical direction.
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if n_columns_diff == -1:
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start = max(node_index + 1, p_node_index)
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tail = ["|", " "] * (start - node_index - 1)
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tail.extend(["/", " "] * (n_columns - start))
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return tail
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else:
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return ["\\", " "] * (n_columns - node_index - 1)
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else:
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return ["|", " "] * (n_columns - node_index - 1)
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def _drawedges(edges, nodeline, interline):
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for (start, end) in edges:
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if start == end + 1:
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interline[2 * end + 1] = "/"
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elif start == end - 1:
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interline[2 * start + 1] = "\\"
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elif start == end:
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interline[2 * start] = "|"
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else:
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|
if 2 * end >= len(nodeline):
|
|
|
continue
|
|
|
nodeline[2 * end] = "+"
|
|
|
if start > end:
|
|
|
(start, end) = (end, start)
|
|
|
for i in range(2 * start + 1, 2 * end):
|
|
|
if nodeline[i] != "+":
|
|
|
nodeline[i] = "-"
|
|
|
|
|
|
def _getpaddingline(ni, n_columns, edges):
|
|
|
line = []
|
|
|
line.extend(["|", " "] * ni)
|
|
|
if (ni, ni - 1) in edges or (ni, ni) in edges:
|
|
|
# (ni, ni - 1) (ni, ni)
|
|
|
# | | | | | | | |
|
|
|
# +---o | | o---+
|
|
|
# | | c | | c | |
|
|
|
# | |/ / | |/ /
|
|
|
# | | | | | |
|
|
|
c = "|"
|
|
|
else:
|
|
|
c = " "
|
|
|
line.extend([c, " "])
|
|
|
line.extend(["|", " "] * (n_columns - ni - 1))
|
|
|
return line
|
|
|
|
|
|
def asciistate():
|
|
|
"""returns the initial value for the "state" argument to ascii()"""
|
|
|
return [0, 0]
|
|
|
|
|
|
def ascii(ui, state, type, char, text, coldata):
|
|
|
"""prints an ASCII graph of the DAG
|
|
|
|
|
|
takes the following arguments (one call per node in the graph):
|
|
|
|
|
|
- ui to write to
|
|
|
- Somewhere to keep the needed state in (init to asciistate())
|
|
|
- Column of the current node in the set of ongoing edges.
|
|
|
- Type indicator of node data, usually 'C' for changesets.
|
|
|
- Payload: (char, lines):
|
|
|
- Character to use as node's symbol.
|
|
|
- List of lines to display as the node's text.
|
|
|
- Edges; a list of (col, next_col) indicating the edges between
|
|
|
the current node and its parents.
|
|
|
- Number of columns (ongoing edges) in the current revision.
|
|
|
- The difference between the number of columns (ongoing edges)
|
|
|
in the next revision and the number of columns (ongoing edges)
|
|
|
in the current revision. That is: -1 means one column removed;
|
|
|
0 means no columns added or removed; 1 means one column added.
|
|
|
"""
|
|
|
|
|
|
idx, edges, ncols, coldiff = coldata
|
|
|
assert -2 < coldiff < 2
|
|
|
if coldiff == -1:
|
|
|
# Transform
|
|
|
#
|
|
|
# | | | | | |
|
|
|
# o | | into o---+
|
|
|
# |X / |/ /
|
|
|
# | | | |
|
|
|
_fixlongrightedges(edges)
|
|
|
|
|
|
# add_padding_line says whether to rewrite
|
|
|
#
|
|
|
# | | | | | | | |
|
|
|
# | o---+ into | o---+
|
|
|
# | / / | | | # <--- padding line
|
|
|
# o | | | / /
|
|
|
# o | |
|
|
|
add_padding_line = (len(text) > 2 and coldiff == -1 and
|
|
|
[x for (x, y) in edges if x + 1 < y])
|
|
|
|
|
|
# fix_nodeline_tail says whether to rewrite
|
|
|
#
|
|
|
# | | o | | | | o | |
|
|
|
# | | |/ / | | |/ /
|
|
|
# | o | | into | o / / # <--- fixed nodeline tail
|
|
|
# | |/ / | |/ /
|
|
|
# o | | o | |
|
|
|
fix_nodeline_tail = len(text) <= 2 and not add_padding_line
|
|
|
|
|
|
# nodeline is the line containing the node character (typically o)
|
|
|
nodeline = ["|", " "] * idx
|
|
|
nodeline.extend([char, " "])
|
|
|
|
|
|
nodeline.extend(
|
|
|
_getnodelineedgestail(idx, state[1], ncols, coldiff,
|
|
|
state[0], fix_nodeline_tail))
|
|
|
|
|
|
# shift_interline is the line containing the non-vertical
|
|
|
# edges between this entry and the next
|
|
|
shift_interline = ["|", " "] * idx
|
|
|
if coldiff == -1:
|
|
|
n_spaces = 1
|
|
|
edge_ch = "/"
|
|
|
elif coldiff == 0:
|
|
|
n_spaces = 2
|
|
|
edge_ch = "|"
|
|
|
else:
|
|
|
n_spaces = 3
|
|
|
edge_ch = "\\"
|
|
|
shift_interline.extend(n_spaces * [" "])
|
|
|
shift_interline.extend([edge_ch, " "] * (ncols - idx - 1))
|
|
|
|
|
|
# draw edges from the current node to its parents
|
|
|
_drawedges(edges, nodeline, shift_interline)
|
|
|
|
|
|
# lines is the list of all graph lines to print
|
|
|
lines = [nodeline]
|
|
|
if add_padding_line:
|
|
|
lines.append(_getpaddingline(idx, ncols, edges))
|
|
|
lines.append(shift_interline)
|
|
|
|
|
|
# make sure that there are as many graph lines as there are
|
|
|
# log strings
|
|
|
while len(text) < len(lines):
|
|
|
text.append("")
|
|
|
if len(lines) < len(text):
|
|
|
extra_interline = ["|", " "] * (ncols + coldiff)
|
|
|
while len(lines) < len(text):
|
|
|
lines.append(extra_interline)
|
|
|
|
|
|
# print lines
|
|
|
indentation_level = max(ncols, ncols + coldiff)
|
|
|
for (line, logstr) in zip(lines, text):
|
|
|
ln = "%-*s %s" % (2 * indentation_level, "".join(line), logstr)
|
|
|
ui.write(ln.rstrip() + '\n')
|
|
|
|
|
|
# ... and start over
|
|
|
state[0] = coldiff
|
|
|
state[1] = idx
|
|
|
|
