# Revision graph generator for Mercurial
#
# Copyright 2008 Dirkjan Ochtman <dirkjan@ochtman.nl>
# Copyright 2007 Joel Rosdahl <joel@rosdahl.net>
#
# 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 __future__ import absolute_import
import heapq
from .node import nullrev
from . import (
revset,
util,
)
CHANGESET = 'C'
def groupbranchiter(revs, parentsfunc, firstbranch=()):
"""Yield revisions from heads to roots one (topo) branch at a time.
This function aims to be used by a graph generator that wishes to minimize
the number of parallel branches and their interleaving.
Example iteration order (numbers show the "true" order in a changelog):
o 4
|
o 1
|
| o 3
| |
| o 2
|/
o 0
Note that the ancestors of merges are understood by the current
algorithm to be on the same branch. This means no reordering will
occur behind a merge.
"""
### 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
# "merges" into an existing one. This reduces the number of parallel
# branches with interleaved revisions.
#
# 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 following logic:
#
# 1) if REV is a parent of (A), we will emit it. If there is a
# retention group ((B) above) that is blocked on REV being
# available, we emit all the revisions out of that retention
# group first.
#
# 2) 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.
#
# 3) finally if no such group existed in (B), we create a new subgroup.
#
#
# To bootstrap the algorithm, we emit the tipmost revision (which
# puts it in group (A) from above).
revs.sort(reverse=True)
# Set of parents of revision that have been emitted. They can be considered
# unblocked as the graph generator is already aware of them so there is no
# need to delay the revisions that reference them.
#
# If someone wants to prioritize a branch over the others, pre-filling this
# set will force all other branches to wait until this branch is ready to be
# emitted.
unblocked = set(firstbranch)
# list of groups 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
# these parents to display the revs in a group.
#
# This first implementation is smart until it encounters a merge: it will
# emit revs as soon as any parent 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 gives up on any special ordering for ancestors
# of merges. The implementation can be improved to handle this better.
#
# The first subgroup is special. It corresponds 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.
groups = [([], unblocked)]
pendingheap = []
pendingset = set()
heapq.heapify(pendingheap)
heappop = heapq.heappop
heappush = heapq.heappush
for currentrev in revs:
# Heap works with smallest element, we want highest so we invert
if currentrev not in pendingset:
heappush(pendingheap, -currentrev)
pendingset.add(currentrev)
# iterates on pending rev until after the current rev have been
# processed.
rev = None
while rev != currentrev:
rev = -heappop(pendingheap)
pendingset.remove(rev)
# Seek for a subgroup blocked, waiting for the current revision.
matching = [i for i, g in enumerate(groups) if rev in g[1]]
if matching:
# The main idea is to gather together all sets that are blocked
# on the same revision.
#
# Groups are merged when a common blocking ancestor is
# observed. For example, given two groups:
#
# revs [5, 4] waiting for 1
# revs [3, 2] waiting for 1
#
# These two groups will be merged when we process
# 1. In theory, we could have merged the groups when
# we added 2 to the group it is now in (we could have
# noticed the groups were both blocked on 1 then), but
# the way it works now makes the algorithm simpler.
#
# We also always keep the oldest subgroup first. We can
# probably improve the behavior by having the longest set
# first. That way, graph algorithms could minimise the length
# of parallel lines their drawing. 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 (except the one we kept)
# (starting from the last subgroup for performance and
# sanity reasons)
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([rev])))
gr = groups[targetidx]
# We now add 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 precede it.
#
# we also update the <parents> set to include the parents of the
# new nodes.
if rev == currentrev: # only display stuff in rev
gr[0].append(rev)
gr[1].remove(rev)
parents = [p for p in parentsfunc(rev) if p > nullrev]
gr[1].update(parents)
for p in parents:
if p not in pendingset:
pendingset.add(p)
heappush(pendingheap, -p)
# Look for a subgroup to display
#
# When unblocked is empty (if clause), we were not waiting for any
# revisions during the first iteration (if no priority was given) or
# if we emitted a whole disconnected set of the graph (reached a
# root). In that case we arbitrarily take the oldest known
# subgroup. The heuristic could probably be better.
#
# Otherwise (elif clause) if the subgroup is blocked on
# a revision we just emitted, we can safely emit it as
# well.
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][:] = []
# Check if we have some subgroup waiting for revisions we are not going to
# iterate over
for g in groups:
for r in g[0]:
yield r
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
gpcache = {}
if repo.ui.configbool('experimental', 'graph-group-branches', False):
firstbranch = ()
firstbranchrevset = repo.ui.config(
'experimental', 'graph-group-branches.firstbranch', '')
if firstbranchrevset:
firstbranch = repo.revs(firstbranchrevset)
parentrevs = repo.changelog.parentrevs
revs = groupbranchiter(revs, parentrevs, firstbranch)
revs = revset.baseset(revs)
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:
# precompute slow query as we know reachableroots() goes
# through all revs (issue4782)
if not isinstance(revs, revset.baseset):
revs = revset.baseset(revs)
gp = gpcache[mpar] = revset.reachableroots(repo, 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 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