mercurial/tagmerge.py
author Augie Fackler <augie@google.com>
Thu, 25 Jan 2018 21:16:28 -0500
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child 36733 66250de006c6
permissions -rw-r--r--
bdiff: write a native version of splitnewlines ./hg perfunidiff mercurial/manifest.py 0 --count 500 --profile before: ! wall 0.309280 comb 0.350000 user 0.290000 sys 0.060000 (best of 32) ./hg perfunidiff mercurial/manifest.py 0 --count 500 --profile after: ! wall 0.241572 comb 0.260000 user 0.240000 sys 0.020000 (best of 39) so it's about 20% faster. I hate Python. I wish we could usefully write this in Rust, but it doesn't look like that's realistic without using the cpython crate, which I'd still like to avoid. Differential Revision: https://phab.mercurial-scm.org/D1973
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# tagmerge.py - merge .hgtags files
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#
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# Copyright 2014 Angel Ezquerra <angel.ezquerra@gmail.com>
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#
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# This software may be used and distributed according to the terms of the
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# GNU General Public License version 2 or any later version.
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# This module implements an automatic merge algorithm for mercurial's tag files
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#
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# The tagmerge algorithm implemented in this module is able to resolve most
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# merge conflicts that currently would trigger a .hgtags merge conflict. The
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# only case that it does not (and cannot) handle is that in which two tags point
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# to different revisions on each merge parent _and_ their corresponding tag
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# histories have the same rank (i.e. the same length). In all other cases the
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# merge algorithm will choose the revision belonging to the parent with the
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# highest ranked tag history. The merged tag history is the combination of both
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# tag histories (special care is taken to try to combine common tag histories
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# where possible).
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#
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# In addition to actually merging the tags from two parents, taking into
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# account the base, the algorithm also tries to minimize the difference
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# between the merged tag file and the first parent's tag file (i.e. it tries to
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# make the merged tag order as as similar as possible to the first parent's tag
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# file order).
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#
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# The algorithm works as follows:
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# 1. read the tags from p1, p2 and the base
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#     - when reading the p1 tags, also get the line numbers associated to each
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#       tag node (these will be used to sort the merged tags in a way that
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#       minimizes the diff to p1). Ignore the file numbers when reading p2 and
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#       the base
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# 2. recover the "lost tags" (i.e. those that are found in the base but not on
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#    p1 or p2) and add them back to p1 and/or p2
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#     - at this point the only tags that are on p1 but not on p2 are those new
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#       tags that were introduced in p1. Same thing for the tags that are on p2
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#       but not on p2
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# 3. take all tags that are only on p1 or only on p2 (but not on the base)
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#     - Note that these are the tags that were introduced between base and p1
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#       and between base and p2, possibly on separate clones
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# 4. for each tag found both on p1 and p2 perform the following merge algorithm:
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#     - the tags conflict if their tag "histories" have the same "rank" (i.e.
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#       length) AND the last (current) tag is NOT the same
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#     - for non conflicting tags:
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#         - choose which are the high and the low ranking nodes
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#             - the high ranking list of nodes is the one that is longer.
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#               In case of draw favor p1
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#             - the merged node list is made of 3 parts:
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#                 - first the nodes that are common to the beginning of both
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#                   the low and the high ranking nodes
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#                 - second the non common low ranking nodes
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#                 - finally the non common high ranking nodes (with the last
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#                   one being the merged tag node)
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#             - note that this is equivalent to putting the whole low ranking
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#               node list first, followed by the non common high ranking nodes
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#     - note that during the merge we keep the "node line numbers", which will
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#       be used when writing the merged tags to the tag file
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# 5. write the merged tags taking into account to their positions in the first
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#    parent (i.e. try to keep the relative ordering of the nodes that come
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#    from p1). This minimizes the diff between the merged and the p1 tag files
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#    This is done by using the following algorithm
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#     - group the nodes for a given tag that must be written next to each other
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#         - A: nodes that come from consecutive lines on p1
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#         - B: nodes that come from p2 (i.e. whose associated line number is
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#              None) and are next to one of the a nodes in A
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#         - each group is associated with a line number coming from p1
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#     - generate a "tag block" for each of the groups
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#         - a tag block is a set of consecutive "node tag" lines belonging to
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#           the same tag and which will be written next to each other on the
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#           merged tags file
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#     - sort the "tag blocks" according to their associated number line
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#         - put blocks whose nodes come all from p2 first
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#     - write the tag blocks in the sorted order
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from __future__ import absolute_import
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import operator
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from .i18n import _
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from .node import (
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    hex,
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    nullid,
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)
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from .import (
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    tags as tagsmod,
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    util,
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)
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hexnullid = hex(nullid)
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def readtagsformerge(ui, repo, lines, fn='', keeplinenums=False):
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    '''read the .hgtags file into a structure that is suitable for merging
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    Depending on the keeplinenums flag, clear the line numbers associated
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    with each tag. This is done because only the line numbers of the first
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    parent are useful for merging.
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    '''
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    filetags = tagsmod._readtaghist(ui, repo, lines, fn=fn, recode=None,
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                                    calcnodelines=True)[1]
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    for tagname, taginfo in filetags.items():
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        if not keeplinenums:
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            for el in taginfo:
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                el[1] = None
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    return filetags
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def grouptagnodesbyline(tagnodes):
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    '''
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    Group nearby nodes (i.e. those that must be written next to each other)
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    The input is a list of [node, position] pairs, corresponding to a given tag
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    The position is the line number where the node was found on the first parent
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    .hgtags file, or None for those nodes that came from the base or the second
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    parent .hgtags files.
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    This function groups those [node, position] pairs, returning a list of
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    groups of nodes that must be written next to each other because their
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    positions are consecutive or have no position preference (because their
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    position is None).
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    The result is a list of [position, [consecutive node list]]
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    '''
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    firstlinenum = None
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    for hexnode, linenum in tagnodes:
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        firstlinenum = linenum
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        if firstlinenum is not None:
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            break
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    if firstlinenum is None:
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        return [[None, [el[0] for el in tagnodes]]]
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    tagnodes[0][1] = firstlinenum
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    groupednodes = [[firstlinenum, []]]
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    prevlinenum = firstlinenum
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    for hexnode, linenum in tagnodes:
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        if linenum is not None and linenum - prevlinenum > 1:
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            groupednodes.append([linenum, []])
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        groupednodes[-1][1].append(hexnode)
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        if linenum is not None:
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            prevlinenum = linenum
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    return groupednodes
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def writemergedtags(fcd, mergedtags):
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    '''
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    write the merged tags while trying to minimize the diff to the first parent
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    This function uses the ordering info stored on the merged tags dict to
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    generate an .hgtags file which is correct (in the sense that its contents
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    correspond to the result of the tag merge) while also being as close as
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    possible to the first parent's .hgtags file.
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    '''
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    # group the node-tag pairs that must be written next to each other
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    for tname, taglist in mergedtags.items():
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        mergedtags[tname] = grouptagnodesbyline(taglist)
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    # convert the grouped merged tags dict into a format that resembles the
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    # final .hgtags file (i.e. a list of blocks of 'node tag' pairs)
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    def taglist2string(tlist, tname):
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        return '\n'.join(['%s %s' % (hexnode, tname) for hexnode in tlist])
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    finaltags = []
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    for tname, tags in mergedtags.items():
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        for block in tags:
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            block[1] = taglist2string(block[1], tname)
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        finaltags += tags
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    # the tag groups are linked to a "position" that can be used to sort them
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    # before writing them
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    # the position is calculated to ensure that the diff of the merged .hgtags
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    # file to the first parent's .hgtags file is as small as possible
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    finaltags.sort(key=operator.itemgetter(0))
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    # finally we can join the sorted groups to get the final contents of the
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    # merged .hgtags file, and then write it to disk
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    mergedtagstring = '\n'.join([tags for rank, tags in finaltags if tags])
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    fcd.write(mergedtagstring + '\n', fcd.flags())
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def singletagmerge(p1nodes, p2nodes):
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    '''
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    merge the nodes corresponding to a single tag
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    Note that the inputs are lists of node-linenum pairs (i.e. not just lists
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    of nodes)
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    '''
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    if not p2nodes:
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        return p1nodes
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    if not p1nodes:
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        return p2nodes
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    # there is no conflict unless both tags point to different revisions
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    # and have a non identical tag history
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    p1currentnode = p1nodes[-1][0]
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    p2currentnode = p2nodes[-1][0]
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    if p1currentnode != p2currentnode and len(p1nodes) == len(p2nodes):
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        # cannot merge two tags with same rank pointing to different nodes
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        return None
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    # which are the highest ranking (hr) / lowest ranking (lr) nodes?
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    if len(p1nodes) >= len(p2nodes):
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        hrnodes, lrnodes = p1nodes, p2nodes
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    else:
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        hrnodes, lrnodes = p2nodes, p1nodes
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    # the lowest ranking nodes will be written first, followed by the highest
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    # ranking nodes
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    # to avoid unwanted tag rank explosion we try to see if there are some
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    # common nodes that can be written only once
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    commonidx = len(lrnodes)
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    for n in range(len(lrnodes)):
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        if hrnodes[n][0] != lrnodes[n][0]:
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            commonidx = n
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            break
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        lrnodes[n][1] = p1nodes[n][1]
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    # the merged node list has 3 parts:
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    # - common nodes
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    # - non common lowest ranking nodes
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    # - non common highest ranking nodes
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    # note that the common nodes plus the non common lowest ranking nodes is the
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    # whole list of lr nodes
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    return lrnodes + hrnodes[commonidx:]
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def merge(repo, fcd, fco, fca):
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    '''
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    Merge the tags of two revisions, taking into account the base tags
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    Try to minimize the diff between the merged tags and the first parent tags
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    '''
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    ui = repo.ui
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    # read the p1, p2 and base tags
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    # only keep the line numbers for the p1 tags
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    p1tags = readtagsformerge(
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        ui, repo, fcd.data().splitlines(), fn="p1 tags",
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        keeplinenums=True)
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    p2tags = readtagsformerge(
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        ui, repo, fco.data().splitlines(), fn="p2 tags",
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        keeplinenums=False)
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    basetags = readtagsformerge(
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        ui, repo, fca.data().splitlines(), fn="base tags",
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        keeplinenums=False)
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    # recover the list of "lost tags" (i.e. those that were found on the base
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    # revision but not on one of the revisions being merged)
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    basetagset = set(basetags)
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    for n, pntags in enumerate((p1tags, p2tags)):
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        pntagset = set(pntags)
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        pnlosttagset = basetagset - pntagset
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        for t in pnlosttagset:
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            pntags[t] = basetags[t]
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            if pntags[t][-1][0] != hexnullid:
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                pntags[t].append([hexnullid, None])
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    conflictedtags = []  # for reporting purposes
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    mergedtags = util.sortdict(p1tags)
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    # sortdict does not implement iteritems()
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    for tname, p2nodes in p2tags.items():
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        if tname not in mergedtags:
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            mergedtags[tname] = p2nodes
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            continue
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        p1nodes = mergedtags[tname]
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        mergednodes = singletagmerge(p1nodes, p2nodes)
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        if mergednodes is None:
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            conflictedtags.append(tname)
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            continue
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        mergedtags[tname] = mergednodes
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    if conflictedtags:
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        numconflicts = len(conflictedtags)
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        ui.warn(_('automatic .hgtags merge failed\n'
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            'the following %d tags are in conflict: %s\n')
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            % (numconflicts, ', '.join(sorted(conflictedtags))))
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        return True, 1
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d1aa3fee4ca4 tagmerge: use workingfilectx to write merged tags
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    writemergedtags(fcd, mergedtags)
21922
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    ui.note(_('.hgtags merged successfully\n'))
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    return False, 0
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