# 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: