##// END OF EJS Templates
interfaces: add the optional `bdiff.xdiffblocks()` method...
interfaces: add the optional `bdiff.xdiffblocks()` method PyCharm flagged where this was called on the protocol class in `mdiff.py` in the previous commit, but pytype completely missed it. PyCharm is correct here, but I'm committing this separately to highlight this potential problem- some of the implementations don't implement _all_ of the methods the others do, and there's not a great way to indicate on a protocol class that a method or attribute is optional- that's kinda the opposite of what static typing is about. Making the method an `Optional[Callable]` attribute works here, and keeps both PyCharm and pytype happy, and the generated `mdiff.pyi` and `modules.pyi` look reasonable. We might be getting a little lucky, because the method isn't invoked directly- it is returned from another method that selects which block function to use. Except since it is declared on the protocol class, every module needs this attribute (in theory, but in practice this doesn't seem to be checked), so the check for it on the module has to change from `hasattr()` to `getattr(..., None)`. We defer defining the optional attrs to the type checking phase as an extra precaution- that way it isn't an attr with a `None` value at runtime if someone is still using `hasattr()`. As to why pytype missed this, I have no clue. The generated `mdiff.pyi` even has the global variable typed as `bdiff: intmod.BDiff`, so uses of it really should comply with what is on the class, protocol class or not.

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stabletailsort.py
174 lines | 5.4 KiB | text/x-python | PythonLexer
# stabletailsort.py - stable ordering of revisions
#
# Copyright 2021-2023 Pacien TRAN-GIRARD <pacien.trangirard@pacien.net>
#
# 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.
"""
from __future__ import annotations
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-Å“dipal parent pair of the given revision.
An Å“dipal 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 Å“dipal parent.
In the second case, p2 is the Å“dipal parent.
Å’dipal 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 Å“dipal 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
px, pt = _parents(cl, cursor_rev)
if pt == nullrev:
cursor_rev = px
else:
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
def _find_all_leaps_naive(cl, head_rev):
"""
Yields the leaps in the stable-tail sort of the given revision.
A leap is a pair of revisions (source, target) consecutive in the
stable-tail sort of a head, for which target != px(source).
Leaps are yielded in the same order as encountered in the stable-tail sort,
from head to root.
"""
sts = _stable_tail_sort_naive(cl, head_rev)
prev = next(sts)
for current in sts:
if current != _parents(cl, prev)[0]:
yield (prev, current)
prev = current
def _find_specific_leaps_naive(cl, head_rev):
"""
Returns the specific leaps in the stable-tail sort of the given revision.
Specific leaps are leaps appear in the stable-tail sort of a given
revision, but not in the stable-tail sort of any of its ancestors.
The final leaps (leading to the pt of the considered merge) are omitted.
Only merge nodes can have associated specific leaps.
This implementations uses the whole leap sets of the given revision and
of its parents.
"""
px, pt = _parents(cl, head_rev)
if px == nullrev or pt == nullrev:
return # linear nodes cannot have specific leaps
parents_leaps = set(_find_all_leaps_naive(cl, px))
sts = _stable_tail_sort_naive(cl, head_rev)
prev = next(sts)
for current in sts:
if current == pt:
break
if current != _parents(cl, prev)[0]:
leap = (prev, current)
if leap not in parents_leaps:
yield leap
prev = current