graphlog: add a way to test the 'groupbranchiter' function

We add an experimental config option to use the topological sorting. I first
tried to hook the 'groupbranchiter' function in the 'sort' revset but this was useless
because graphlog enforces revision number sorting :(

As the goal is to advance on the topological iteration logic, I see this
experimental option as a good way to move forward.

We have to use turn the iterator into a list because the graphlog is apparently
not ready for pure iterator input yet.

tests/test-glog-topological.t

@@ -0,0 +1,58 b''
+This test file aims at test topological iteration and the various configuration it can has.
+
+  $ cat >> $HGRCPATH << EOF
+  > [ui]
+  > logtemplate={rev}\n
+  > EOF
+
+On this simple example, all topological branch are displayed in turn until we
+can finally display 0. this implies skipping from 8 to 3 and coming back to 7
+later.
+
+  $ hg init test01
+  $ cd test01
+  $ hg unbundle $TESTDIR/bundles/remote.hg
+  adding changesets
+  adding manifests
+  adding file changes
+  added 9 changesets with 7 changes to 4 files (+1 heads)
+  (run 'hg heads' to see heads, 'hg merge' to merge)
+
+  $ hg log -G
+  o  8
+  |
+  | o  7
+  | |
+  | o  6
+  | |
+  | o  5
+  | |
+  | o  4
+  | |
+  o |  3
+  | |
+  o |  2
+  | |
+  o |  1
+  |/
+  o  0
+  
+  $ hg --config experimental.graph-topological=1 log -G
+  o  8
+  |
+  o  3
+  |
+  o  2
+  |
+  o  1
+  |
+  | o  7
+  | |
+  | o  6
+  | |
+  | o  5
+  | |
+  | o  4
+  |/
+  o  0
+  

mercurial/graphmod.py

@@ -1,529 +1,532 b''
 # Revision graph generator for Mercurial
 #
 # Copyright 2008 Dirkjan Ochtman <[e-mail]>
 # Copyright 2007 Joel Rosdahl <[e-mail]>
 #
 # This software may be used and distributed according to the terms of the
 # GNU General Public License version 2 or any later version.
 
 """supports walking the history as DAGs suitable for graphical output
 
 The most basic format we use is that of::
 
   (id, type, data, [parentids])
 
 The node and parent ids are arbitrary integers which identify a node in the
 context of the graph returned. Type is a constant specifying the node type.
 Data depends on type.
 """
 
 from mercurial.node import nullrev
 import util
 
 CHANGESET = 'C'
 
 def groupbranchiter(revs, parentsfunc):
     """yield revision from heads to roots one (topo) branch after the other.
 
     This function aims to be used by a graph generator that wishes to minimize
     the amount of parallel branches and their interleaving.
 
     Example iteration order:
 
       o  4
       |
       o  1
       |
       | o  3
       | |
       | o  2
       |/
       o  0
 
     Currently does not handle non-contiguous <revs> input.
 
     Currently consider every changeset under a merge to be on the same branch
     using revision number to sort them.
 
     Could be easily extend to give priority to an initial branch."""
     ### Quick summary of the algorithm
     #
     # This function is based around a "retention" principle. We keep revisions
     # in memory until we are ready to emit a whole branch that immediately
     # "merge" into an existing one. This reduce the number of branch "ongoing"
     # at the same time.
     #
     # During iteration revs are split into two groups:
     # A) revision already emitted
     # B) revision in "retention". They are stored as different subgroups.
     #
     # for each REV, we do the follow logic:
     #
     #   a) if REV is a parent of (A), we will emit it. But before emitting it,
     #   we'll "free" all the revs from subgroup in (B) that were waiting for
     #   REV to be available. So we emit all revision of such subgroup before
     #   emitting REV
     #
     #   b) else, we'll search for a subgroup in (B) awaiting for REV to be
     #   available, if such subgroup exist, we add REV to it and the subgroup is
     #   now awaiting for REV.parents() to be available.
     #
     #   c) finally if no such group existed in (B), we create a new subgroup.
     #
     #
     # To bootstrap the algorithm, we emit the tipmost revision.
 
     revs.sort(reverse=True)
 
     # Set of parents of revision that have been yield. They can be considered
     # unblocked as the graph generator is already aware of them so there is no
     # need to delay the one that reference them.
     unblocked = set()
 
     # list of group waiting to be displayed, each group is defined by:
     #
     #   (revs:    lists of revs waiting to be displayed,
     #    blocked: set of that cannot be displayed before those in 'revs')
     #
     # The second value ('blocked') correspond to parents of any revision in the
     # group ('revs') that is not itself contained in the group. The main idea
     # of this algorithm is to delay as much as possible the emission of any
     # revision.  This means waiting for the moment we are about to display
     # theses parents to display the revs in a group.
     #
     # This first implementation is smart until it meet a merge: it will emit
     # revs as soon as any parents is about to be emitted and can grow an
     # arbitrary number of revs in 'blocked'. In practice this mean we properly
     # retains new branches but give up on any special ordering for ancestors of
     # merges. The implementation can be improved to handle this better.
     #
     # The first subgroup is special. It correspond to all the revision that
     # were already emitted. The 'revs' lists is expected to be empty and the
     # 'blocked' set contains the parents revisions of already emitted revision.
     #
     # You could pre-seed the <parents> set of groups[0] to a specific
     # changesets to select what the first emitted branch should be.
     #
     # We do not support revisions will hole yet, but adding such support would
     # be easy. The iteration will have to be done using both input revision and
     # parents (see cl.ancestors function + a few tweaks) but only revisions
     # parts of the initial set should be emitted.
     groups = [([], unblocked)]
     for current in revs:
         # Look for a subgroup blocked, waiting for the current revision.
         matching = [i for i, g in enumerate(groups) if current in g[1]]
 
         if matching:
             # The main idea is to gather together all sets that await on the
             # same revision.
             #
             # This merging is done at the time we are about to add this common
             # awaited to the subgroup for simplicity purpose. Such merge could
             # happen sooner when we update the "blocked" set of revision.
             #
             # We also always keep the oldest subgroup first. We can probably
             # improve the behavior by having the longuest set first. That way,
             # graph algorythms could minimise the length of parallele lines
             # their draw. This is currently not done.
             targetidx = matching.pop(0)
             trevs, tparents = groups[targetidx]
             for i in matching:
                 gr = groups[i]
                 trevs.extend(gr[0])
                 tparents |= gr[1]
             # delete all merged subgroups (but the one we keep)
             # (starting from the last subgroup for performance and sanity reason)
             for i in reversed(matching):
                 del groups[i]
         else:
             # This is a new head. We create a new subgroup for it.
             targetidx = len(groups)
             groups.append(([], set([current])))
 
         gr = groups[targetidx]
 
         # We now adds the current nodes to this subgroups. This is done after
         # the subgroup merging because all elements from a subgroup that relied
         # on this rev must preceed it.
         #
         # we also update the <parents> set to includes the parents on the
         # new nodes.
         gr[0].append(current)
         gr[1].remove(current)
         gr[1].update([p for p in parentsfunc(current) if p > nullrev])
 
         # Look for a subgroup to display
         #
         # When unblocked is empty (if clause), We are not waiting over any
         # revision during the first iteration (if no priority was given) or if
         # we outputed a whole disconnected sets of the graph (reached a root).
         # In that case we arbitrarily takes the oldest known subgroup. The
         # heuristique could probably be better.
         #
         # Otherwise (elif clause) this mean we have some emitted revision.  if
         # the subgroup awaits on the same revision that the outputed ones, we
         # can safely output it.
         if not unblocked:
             if len(groups) > 1:  # display other subset
                 targetidx = 1
                 gr = groups[1]
         elif not gr[1] & unblocked:
             gr = None
 
         if gr is not None:
             # update the set of awaited revisions with the one from the
             # subgroup
             unblocked |= gr[1]
             # output all revisions in the subgroup
             for r in gr[0]:
                 yield r
             # delete the subgroup that you just output
             # unless it is groups[0] in which case you just empty it.
             if targetidx:
                 del groups[targetidx]
             else:
                 gr[0][:] = []
 
 def dagwalker(repo, revs):
     """cset DAG generator yielding (id, CHANGESET, ctx, [parentids]) tuples
 
     This generator function walks through revisions (which should be ordered
     from bigger to lower). It returns a tuple for each node. The node and parent
     ids are arbitrary integers which identify a node in the context of the graph
     returned.
     """
     if not revs:
         return
 
     cl = repo.changelog
     lowestrev = revs.min()
     gpcache = {}
 
+    if repo.ui.configbool('experimental', 'graph-topological', False):
+        revs = list(groupbranchiter(revs, repo.changelog.parentrevs))
+
     for rev in revs:
         ctx = repo[rev]
         parents = sorted(set([p.rev() for p in ctx.parents()
                               if p.rev() in revs]))
         mpars = [p.rev() for p in ctx.parents() if
                  p.rev() != nullrev and p.rev() not in parents]
 
         for mpar in mpars:
             gp = gpcache.get(mpar)
             if gp is None:
                 gp = gpcache[mpar] = grandparent(cl, lowestrev, revs, mpar)
             if not gp:
                 parents.append(mpar)
             else:
                 parents.extend(g for g in gp if g not in parents)
 
         yield (ctx.rev(), CHANGESET, ctx, parents)
 
 def nodes(repo, nodes):
     """cset DAG generator yielding (id, CHANGESET, ctx, [parentids]) tuples
 
     This generator function walks the given nodes. It only returns parents
     that are in nodes, too.
     """
     include = set(nodes)
     for node in nodes:
         ctx = repo[node]
         parents = set([p.rev() for p in ctx.parents() if p.node() in include])
         yield (ctx.rev(), CHANGESET, ctx, sorted(parents))
 
 def colored(dag, repo):
     """annotates a DAG with colored edge information
 
     For each DAG node this function emits tuples::
 
       (id, type, data, (col, color), [(col, nextcol, color)])
 
     with the following new elements:
 
       - Tuple (col, color) with column and color index for the current node
       - A list of tuples indicating the edges between the current node and its
         parents.
     """
     seen = []
     colors = {}
     newcolor = 1
     config = {}
 
     for key, val in repo.ui.configitems('graph'):
         if '.' in key:
             branch, setting = key.rsplit('.', 1)
             # Validation
             if setting == "width" and val.isdigit():
                 config.setdefault(branch, {})[setting] = int(val)
             elif setting == "color" and val.isalnum():
                 config.setdefault(branch, {})[setting] = val
 
     if config:
         getconf = util.lrucachefunc(
             lambda rev: config.get(repo[rev].branch(), {}))
     else:
         getconf = lambda rev: {}
 
     for (cur, type, data, parents) in dag:
 
         # Compute seen and next
         if cur not in seen:
             seen.append(cur) # new head
             colors[cur] = newcolor
             newcolor += 1
 
         col = seen.index(cur)
         color = colors.pop(cur)
         next = seen[:]
 
         # Add parents to next
         addparents = [p for p in parents if p not in next]
         next[col:col + 1] = addparents
 
         # Set colors for the parents
         for i, p in enumerate(addparents):
             if not i:
                 colors[p] = color
             else:
                 colors[p] = newcolor
                 newcolor += 1
 
         # Add edges to the graph
         edges = []
         for ecol, eid in enumerate(seen):
             if eid in next:
                 bconf = getconf(eid)
                 edges.append((
                     ecol, next.index(eid), colors[eid],
                     bconf.get('width', -1),
                     bconf.get('color', '')))
             elif eid == cur:
                 for p in parents:
                     bconf = getconf(p)
                     edges.append((
                         ecol, next.index(p), color,
                         bconf.get('width', -1),
                         bconf.get('color', '')))
 
         # Yield and move on
         yield (cur, type, data, (col, color), edges)
         seen = next
 
 def grandparent(cl, lowestrev, roots, head):
     """Return all ancestors of head in roots which revision is
     greater or equal to lowestrev.
     """
     pending = set([head])
     seen = set()
     kept = set()
     llowestrev = max(nullrev, lowestrev)
     while pending:
         r = pending.pop()
         if r >= llowestrev and r not in seen:
             if r in roots:
                 kept.add(r)
             else:
                 pending.update([p for p in cl.parentrevs(r)])
             seen.add(r)
     return sorted(kept)
 
 def asciiedges(type, char, lines, seen, rev, parents):
     """adds edge info to changelog DAG walk suitable for ascii()"""
     if rev not in seen:
         seen.append(rev)
     nodeidx = seen.index(rev)
 
     knownparents = []
     newparents = []
     for parent in parents:
         if parent in seen:
             knownparents.append(parent)
         else:
             newparents.append(parent)
 
     ncols = len(seen)
     nextseen = seen[:]
     nextseen[nodeidx:nodeidx + 1] = newparents
     edges = [(nodeidx, nextseen.index(p)) for p in knownparents if p != nullrev]
 
     while len(newparents) > 2:
         # ascii() only knows how to add or remove a single column between two
         # calls. Nodes with more than two parents break this constraint so we
         # introduce intermediate expansion lines to grow the active node list
         # slowly.
         edges.append((nodeidx, nodeidx))
         edges.append((nodeidx, nodeidx + 1))
         nmorecols = 1
         yield (type, char, lines, (nodeidx, edges, ncols, nmorecols))
         char = '\\'
         lines = []
         nodeidx += 1
         ncols += 1
         edges = []
         del newparents[0]
 
     if len(newparents) > 0:
         edges.append((nodeidx, nodeidx))
     if len(newparents) > 1:
         edges.append((nodeidx, nodeidx + 1))
     nmorecols = len(nextseen) - ncols
     seen[:] = nextseen
     yield (type, char, lines, (nodeidx, edges, ncols, nmorecols))
 
 def _fixlongrightedges(edges):
     for (i, (start, end)) in enumerate(edges):
         if end > start:
             edges[i] = (start, end + 1)
 
 def _getnodelineedgestail(
         node_index, p_node_index, n_columns, n_columns_diff, p_diff, fix_tail):
     if fix_tail and n_columns_diff == p_diff and n_columns_diff != 0:
         # Still going in the same non-vertical direction.
         if n_columns_diff == -1:
             start = max(node_index + 1, p_node_index)
             tail = ["|", " "] * (start - node_index - 1)
             tail.extend(["/", " "] * (n_columns - start))
             return tail
         else:
             return ["\\", " "] * (n_columns - node_index - 1)
     else:
         return ["|", " "] * (n_columns - node_index - 1)
 
 def _drawedges(edges, nodeline, interline):
     for (start, end) in edges:
         if start == end + 1:
             interline[2 * end + 1] = "/"
         elif start == end - 1:
             interline[2 * start + 1] = "\\"
         elif start == end:
             interline[2 * start] = "|"
         else:
             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