stabletailgraph: extract _parents util func

mercurial/stabletailgraph/stabletailsort.py

@@ -1,116 +1,120
 # stabletailsort.py - stable ordering of revisions
 #
 # Copyright 2021-2023 Pacien TRAN-GIRARD <[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.
 
 """
 Stable-tail sort computation.
 
 The "stable-tail sort", or STS, is a reverse topological ordering of the
 ancestors of a node, which tends to share large suffixes with the stable-tail
 sort of ancestors and other nodes, giving it its name.
 
 Its properties should make it suitable for making chunks of ancestors with high
 reuse and incrementality for example.
 
 This module and implementation are experimental. Most functions are not yet
 optimised to operate on large production graphs.
 """
 
 import itertools
 from ..node import nullrev
 from .. import ancestor
 
 
 def _sorted_parents(cl, p1, p2):
     """
     Chooses and returns the pair (px, pt) from (p1, p2).
 
     Where
     "px" denotes the parent starting the "exclusive" part, and
     "pt" denotes the parent starting the "Tail" part.
 
     "px" is chosen as the parent with the lowest rank with the goal of
     minimising the size of the exclusive part and maximise the size of the
     tail part, hopefully reducing the overall complexity of the stable-tail
     sort.
 
     In case of equal ranks, the stable node ID is used as a tie-breaker.
     """
     r1, r2 = cl.fast_rank(p1), cl.fast_rank(p2)
     if r1 < r2:
         return (p1, p2)
     elif r1 > r2:
         return (p2, p1)
     elif cl.node(p1) < cl.node(p2):
         return (p1, p2)
     else:
         return (p2, p1)
 
 
 def _nonoedipal_parent_revs(cl, rev):
     """
     Returns the non-œdipal parent pair of the given revision.
 
     An œdipal merge is a merge with parents p1, p2 with either
     p1 in ancestors(p2) or p2 in ancestors(p1).
     In the first case, p1 is the œdipal parent.
     In the second case, p2 is the œdipal parent.
 
     Œdipal edges start empty exclusive parts. They do not bring new ancestors.
     As such, they can be skipped when computing any topological sort or any
     iteration over the ancestors of a node.
 
     The œdipal edges are eliminated here using the rank information.
     """
     p1, p2 = cl.parentrevs(rev)
     if p1 == nullrev or cl.fast_rank(p2) == cl.fast_rank(rev) - 1:
         return p2, nullrev
     elif p2 == nullrev or cl.fast_rank(p1) == cl.fast_rank(rev) - 1:
         return p1, nullrev
     else:
         return p1, p2
 
 
+def _parents(cl, rev):
+    p1, p2 = _nonoedipal_parent_revs(cl, rev)
+    if p2 == nullrev:
+        return p1, p2
+
+    return _sorted_parents(cl, p1, p2)
+
+
 def _stable_tail_sort_naive(cl, head_rev):
     """
     Naive topological iterator of the ancestors given by the stable-tail sort.
 
     The stable-tail sort of a node "h" is defined as the sequence:
     sts(h) := [h] + excl(h) + sts(pt(h))
     where excl(h) := u for u in sts(px(h)) if u not in ancestors(pt(h))
 
     This implementation uses a call-stack whose size is
     O(number of open merges).
 
     As such, this implementation exists mainly as a defining reference.
     """
     cursor_rev = head_rev
     while cursor_rev != nullrev:
         yield cursor_rev
 
-        p1, p2 = _nonoedipal_parent_revs(cl, cursor_rev)
-        if p1 == nullrev:
-            cursor_rev = p2
-        elif p2 == nullrev:
-            cursor_rev = p1
+        px, pt = _parents(cl, cursor_rev)
+        if pt == nullrev:
+            cursor_rev = px
         else:
-            px, pt = _sorted_parents(cl, p1, p2)
-
             tail_ancestors = ancestor.lazyancestors(
                 cl.parentrevs, (pt,), inclusive=True
             )
             exclusive_ancestors = (
                 a
                 for a in _stable_tail_sort_naive(cl, px)
                 if a not in tail_ancestors
             )
 
             # Notice that excl(cur) is disjoint from ancestors(pt),
             # so there is no double-counting:
             # rank(cur) = len([cur]) + len(excl(cur)) + rank(pt)
             excl_part_size = cl.fast_rank(cursor_rev) - cl.fast_rank(pt) - 1
             yield from itertools.islice(exclusive_ancestors, excl_part_size)
             cursor_rev = pt