# Code dedicated to debug commands around evolution

#

# Copyright 2017 Pierre-Yves David <pierre-yves.david@ens-lyon.org>

#

# This software may be used and distributed according to the terms of the

# GNU General Public License version 2 or any later version.

# Status: Ready to Upstream

#

#  * We could have the same code in core as `hg debugobsolete --stat`,

#  * We probably want a way for the extension to hook in for extra data.

from mercurial import (

    obsolete,

    node,

)

from mercurial.i18n import _

from . import exthelper

eh = exthelper.exthelper()

@eh.command('debugobsstorestat', [], '')

def cmddebugobsstorestat(ui, repo):

    """print statistics about obsolescence markers in the repo"""

    def _updateclustermap(nodes, mark, clustersmap):

        c = (set(nodes), set([mark]))

        toproceed = set(nodes)

        while toproceed:

            n = toproceed.pop()

            other = clustersmap.get(n)

            if (other is not None

                and other is not c):

                other[0].update(c[0])

                other[1].update(c[1])

                for on in c[0]:

                    if on in toproceed:

                        continue

                    clustersmap[on] = other

                c = other

            clustersmap[n] = c

    store = repo.obsstore

    unfi = repo.unfiltered()

    nm = unfi.changelog.nodemap

    nbmarkers = len(store._all)

    ui.write(_('markers total:              %9i\n') % nbmarkers)

    sucscount = [0, 0, 0, 0]

    known = 0

    parentsdata = 0

    metakeys = {}

    # node -> cluster mapping

    #   a cluster is a (set(nodes), set(markers)) tuple

    clustersmap = {}

    # same data using parent information

    pclustersmap = {}

    size_v0 = []

    size_v1 = []

    for mark in store:

        if mark[0] in nm:

            known += 1

        nbsucs = len(mark[1])

        sucscount[min(nbsucs, 3)] += 1

        meta = mark[3]

        for key, value in meta:

            metakeys.setdefault(key, 0)

            metakeys[key] += 1

        meta = dict(meta)

        parents = [meta.get('p1'), meta.get('p2')]

        parents = [node.bin(p) for p in parents if p is not None]

        if parents:

            parentsdata += 1

        # cluster handling

        nodes = set(mark[1])

        nodes.add(mark[0])

        _updateclustermap(nodes, mark, clustersmap)

        # same with parent data

        nodes.update(parents)

        _updateclustermap(nodes, mark, pclustersmap)

        size_v0.append(len(obsolete._fm0encodeonemarker(mark)))

        size_v1.append(len(obsolete._fm1encodeonemarker(mark)))

    # freezing the result

    for c in clustersmap.values():

        fc = (frozenset(c[0]), frozenset(c[1]))

        for n in fc[0]:

            clustersmap[n] = fc

    # same with parent data

    for c in pclustersmap.values():

        fc = (frozenset(c[0]), frozenset(c[1]))

        for n in fc[0]:

            pclustersmap[n] = fc

    numobs = len(unfi.revs('obsolete()'))

    numtotal = len(unfi)

    ui.write(('    for known precursors:   %9i' % known))

    ui.write((' (%i/%i obsolete changesets)\n' % (numobs, numtotal)))

    ui.write(('    with parents data:      %9i\n' % parentsdata))

    # successors data

    ui.write(('markers with no successors: %9i\n' % sucscount[0]))

    ui.write(('              1 successors: %9i\n' % sucscount[1]))

    ui.write(('              2 successors: %9i\n' % sucscount[2]))

    ui.write(('    more than 2 successors: %9i\n' % sucscount[3]))

    # meta data info

    ui.write(('    available  keys:\n'))

    for key in sorted(metakeys):

        ui.write(('    %15s:        %9i\n' % (key, metakeys[key])))

    size_v0.sort()

    size_v1.sort()

    if size_v0:

        ui.write('marker size:\n')

        # format v1

        ui.write('    format v1:\n')

        ui.write(('        smallest length:    %9i\n' % size_v1[0]))

        ui.write(('        longer length:      %9i\n' % size_v1[-1]))

        median = size_v1[nbmarkers // 2]

        ui.write(('        median length:      %9i\n' % median))

        mean = sum(size_v1) // nbmarkers

        ui.write(('        mean length:        %9i\n' % mean))

        # format v0

        ui.write('    format v0:\n')

        ui.write(('        smallest length:    %9i\n' % size_v0[0]))

        ui.write(('        longer length:      %9i\n' % size_v0[-1]))

        median = size_v0[nbmarkers // 2]

        ui.write(('        median length:      %9i\n' % median))

        mean = sum(size_v0) // nbmarkers

        ui.write(('        mean length:        %9i\n' % mean))

    allclusters = list(set(clustersmap.values()))

    allclusters.sort(key=lambda x: len(x[1]))

    ui.write(('disconnected clusters:      %9i\n' % len(allclusters)))

    ui.write('        any known node:     %9i\n'

             % len([c for c in allclusters

                    if [n for n in c[0] if nm.get(n) is not None]]))

    if allclusters:

        nbcluster = len(allclusters)

        ui.write(('        smallest length:    %9i\n' % len(allclusters[0][1])))

        ui.write(('        longer length:      %9i\n'

                 % len(allclusters[-1][1])))

        median = len(allclusters[nbcluster // 2][1])

        ui.write(('        median length:      %9i\n' % median))

        mean = sum(len(x[1]) for x in allclusters) // nbcluster

        ui.write(('        mean length:        %9i\n' % mean))

    allpclusters = list(set(pclustersmap.values()))

    allpclusters.sort(key=lambda x: len(x[1]))

    ui.write(('    using parents data:     %9i\n' % len(allpclusters)))

    ui.write('        any known node:     %9i\n'

             % len([c for c in allclusters

                    if [n for n in c[0] if nm.get(n) is not None]]))

    if allpclusters:

        nbcluster = len(allpclusters)

        ui.write(('        smallest length:    %9i\n'

                 % len(allpclusters[0][1])))

        ui.write(('        longer length:      %9i\n'

                 % len(allpclusters[-1][1])))

        median = len(allpclusters[nbcluster // 2][1])

        ui.write(('        median length:      %9i\n' % median))

        mean = sum(len(x[1]) for x in allpclusters) // nbcluster

        ui.write(('        mean length:        %9i\n' % mean))