view mercurial/graphmod.py @ 28487:98d98a645e9d

changelog: add class to represent parsed changelog revisions

Currently, changelog entries are parsed into their respective
components at read time. Many operations are only interested
in a subset of fields of a changelog entry. The parsing and
storing of all the fields adds avoidable overhead.

This patch introduces the "changelogrevision" class. It takes
changelog raw text and exposes the parsed results as attributes.
The code for parsing changelog entries has been moved into its
construction function. changelog.read() has been modified to use
the new class internally while maintaining its existing API.
Future patches will make revision parsing lazy.

We implement the construction function of the new class with
__new__ instead of __init__ so we can use a named tuple to
represent the empty revision. This saves overhead and complexity
of coercing later versions of this class to represent an empty
instance.

While we are here, we add a method on changelog to obtain an
instance of the new type.

The overhead of constructing the new class regresses performance
of revsets accessing this data:

author(mpm)
0.896565
0.929984

desc(bug)
0.887169
0.935642 105%

date(2015)
0.878797
0.908094

extra(rebase_source)
0.865446
0.922624 106%

author(mpm) or author(greg)
1.801832
1.902112 105%

author(mpm) or desc(bug)
1.812438
1.860977

date(2015) or branch(default)
0.968276
1.005824

author(mpm) or desc(bug) or date(2015) or extra(rebase_source)
3.656193
3.743381

Once lazy parsing is implemented, these revsets will all be faster
than before. There is no performance change on revsets that do not
access this data. There /could/ be a performance regression on
operations that perform several changelog reads. However, I can't
think of anything outside of revsets and `hg log` (basically the
same as a revset) that would be impacted.

# 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 __future__ import absolute_import

import heapq

from .node import nullrev
from . import (
    revset,
    util,
)

CHANGESET = 'C'
PARENT = 'P'
GRANDPARENT = 'G'
MISSINGPARENT = 'M'

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, [parentinfo]) tuples

    This generator function walks through revisions (which should be ordered
    from bigger to lower). It returns a tuple for each node.

    Each parentinfo entry is a tuple with (edgetype, parentid), where edgetype
    is one of PARENT, GRANDPARENT or MISSINGPARENT. 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]
        # partition into parents in the rev set and missing parents, then
        # augment the lists with markers, to inform graph drawing code about
        # what kind of edge to draw between nodes.
        pset = 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 pset]
        parents = [(PARENT, p) for p in sorted(pset)]

        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] = sorted(set(revset.reachableroots(
                    repo, revs, [mpar])))
            if not gp:
                parents.append((MISSINGPARENT, mpar))
                pset.add(mpar)
            else:
                parents.extend((GRANDPARENT, g) for g in gp if g not in pset)
                pset.update(gp)

        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((PARENT, 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 pt, 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 ptype, 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, state, rev, parents):
    """adds edge info to changelog DAG walk suitable for ascii()"""
    seen = state['seen']
    if rev not in seen:
        seen.append(rev)
    nodeidx = seen.index(rev)

    knownparents = []
    newparents = []
    for ptype, 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 {'seen': [], 'lastcoldiff': 0, 'lastindex': 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['lastindex'], ncols, coldiff,
                              state['lastcoldiff'], 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['lastcoldiff'] = coldiff
    state['lastindex'] = idx