Mercurial > hg
view tests/test-ancestor.py @ 47072:4c041c71ec01
revlog: introduce an explicit tracking of what the revlog is about
Since the dawn of time, people have been forced to rely to lossy introspection
of the index filename to determine what the purpose and role of the revlog they
encounter is. This is hacky, error prone, inflexible, abstraction-leaky,
<insert-your-own-complaints-here>.
In f63299ee7e4d Raphaël introduced a new attribute to track this information:
`revlog_kind`. However it is initialized in an odd place and various instances
end up not having it set. In addition is only tracking some of the information
we end up having to introspect in various pieces of code.
So we add a new attribute that holds more data and is more strictly enforced.
This work is done in collaboration with Raphaël.
The `revlog_kind` one will be removed/adapted in the next changeset. We expect
to be able to clean up various existing piece of code and to simplify coming
work around the newer revlog format.
Differential Revision: https://phab.mercurial-scm.org/D10352
author | Pierre-Yves David <pierre-yves.david@octobus.net> |
---|---|
date | Tue, 06 Apr 2021 05:20:24 +0200 |
parents | 89a2afe31e82 |
children | 6000f5b25c9b |
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from __future__ import absolute_import, print_function import binascii import getopt import math import os import random import sys import time from mercurial.node import nullrev from mercurial import ( ancestor, debugcommands, hg, pycompat, ui as uimod, util, ) if pycompat.ispy3: long = int xrange = range def buildgraph(rng, nodes=100, rootprob=0.05, mergeprob=0.2, prevprob=0.7): """nodes: total number of nodes in the graph rootprob: probability that a new node (not 0) will be a root mergeprob: probability that, excluding a root a node will be a merge prevprob: probability that p1 will be the previous node return value is a graph represented as an adjacency list. """ graph = [None] * nodes for i in xrange(nodes): if i == 0 or rng.random() < rootprob: graph[i] = [nullrev] elif i == 1: graph[i] = [0] elif rng.random() < mergeprob: if i == 2 or rng.random() < prevprob: # p1 is prev p1 = i - 1 else: p1 = rng.randrange(i - 1) p2 = rng.choice(list(range(0, p1)) + list(range(p1 + 1, i))) graph[i] = [p1, p2] elif rng.random() < prevprob: graph[i] = [i - 1] else: graph[i] = [rng.randrange(i - 1)] return graph def buildancestorsets(graph): ancs = [None] * len(graph) for i in xrange(len(graph)): ancs[i] = {i} if graph[i] == [nullrev]: continue for p in graph[i]: ancs[i].update(ancs[p]) return ancs class naiveincrementalmissingancestors(object): def __init__(self, ancs, bases): self.ancs = ancs self.bases = set(bases) def addbases(self, newbases): self.bases.update(newbases) def removeancestorsfrom(self, revs): for base in self.bases: if base != nullrev: revs.difference_update(self.ancs[base]) revs.discard(nullrev) def missingancestors(self, revs): res = set() for rev in revs: if rev != nullrev: res.update(self.ancs[rev]) for base in self.bases: if base != nullrev: res.difference_update(self.ancs[base]) return sorted(res) def test_missingancestors(seed, rng): # empirically observed to take around 1 second graphcount = 100 testcount = 10 inccount = 10 nerrs = [0] # the default mu and sigma give us a nice distribution of mostly # single-digit counts (including 0) with some higher ones def lognormrandom(mu, sigma): return int(math.floor(rng.lognormvariate(mu, sigma))) def samplerevs(nodes, mu=1.1, sigma=0.8): count = min(lognormrandom(mu, sigma), len(nodes)) return rng.sample(nodes, count) def err(seed, graph, bases, seq, output, expected): if nerrs[0] == 0: print('seed:', hex(seed)[:-1], file=sys.stderr) if gerrs[0] == 0: print('graph:', graph, file=sys.stderr) print('* bases:', bases, file=sys.stderr) print('* seq: ', seq, file=sys.stderr) print('* output: ', output, file=sys.stderr) print('* expected:', expected, file=sys.stderr) nerrs[0] += 1 gerrs[0] += 1 for g in xrange(graphcount): graph = buildgraph(rng) ancs = buildancestorsets(graph) gerrs = [0] for _ in xrange(testcount): # start from nullrev to include it as a possibility graphnodes = range(nullrev, len(graph)) bases = samplerevs(graphnodes) # fast algorithm inc = ancestor.incrementalmissingancestors(graph.__getitem__, bases) # reference slow algorithm naiveinc = naiveincrementalmissingancestors(ancs, bases) seq = [] for _ in xrange(inccount): if rng.random() < 0.2: newbases = samplerevs(graphnodes) seq.append(('addbases', newbases)) inc.addbases(newbases) naiveinc.addbases(newbases) if rng.random() < 0.4: # larger set so that there are more revs to remove from revs = samplerevs(graphnodes, mu=1.5) seq.append(('removeancestorsfrom', revs)) hrevs = set(revs) rrevs = set(revs) inc.removeancestorsfrom(hrevs) naiveinc.removeancestorsfrom(rrevs) if hrevs != rrevs: err( seed, graph, bases, seq, sorted(hrevs), sorted(rrevs), ) else: revs = samplerevs(graphnodes) seq.append(('missingancestors', revs)) h = inc.missingancestors(revs) r = naiveinc.missingancestors(revs) if h != r: err(seed, graph, bases, seq, h, r) # graph is a dict of child->parent adjacency lists for this graph: # o 13 # | # | o 12 # | | # | | o 11 # | | |\ # | | | | o 10 # | | | | | # | o---+ | 9 # | | | | | # o | | | | 8 # / / / / # | | o | 7 # | | | | # o---+ | 6 # / / / # | | o 5 # | |/ # | o 4 # | | # o | 3 # | | # | o 2 # |/ # o 1 # | # o 0 graph = { 0: [-1, -1], 1: [0, -1], 2: [1, -1], 3: [1, -1], 4: [2, -1], 5: [4, -1], 6: [4, -1], 7: [4, -1], 8: [-1, -1], 9: [6, 7], 10: [5, -1], 11: [3, 7], 12: [9, -1], 13: [8, -1], } def test_missingancestors_explicit(): """A few explicit cases, easier to check for catching errors in refactors. The bigger graph at the end has been produced by the random generator above, and we have some evidence that the other tests don't cover it. """ for i, (bases, revs) in enumerate( ( ({1, 2, 3, 4, 7}, set(xrange(10))), ({10}, set({11, 12, 13, 14})), ({7}, set({1, 2, 3, 4, 5})), ) ): print("%% removeancestorsfrom(), example %d" % (i + 1)) missanc = ancestor.incrementalmissingancestors(graph.get, bases) missanc.removeancestorsfrom(revs) print("remaining (sorted): %s" % sorted(list(revs))) for i, (bases, revs) in enumerate( ( ({10}, {11}), ({11}, {10}), ({7}, {9, 11}), ) ): print("%% missingancestors(), example %d" % (i + 1)) missanc = ancestor.incrementalmissingancestors(graph.get, bases) print("return %s" % missanc.missingancestors(revs)) print("% removeancestorsfrom(), bigger graph") vecgraph = [ [-1, -1], [0, -1], [1, 0], [2, 1], [3, -1], [4, -1], [5, 1], [2, -1], [7, -1], [8, -1], [9, -1], [10, 1], [3, -1], [12, -1], [13, -1], [14, -1], [4, -1], [16, -1], [17, -1], [18, -1], [19, 11], [20, -1], [21, -1], [22, -1], [23, -1], [2, -1], [3, -1], [26, 24], [27, -1], [28, -1], [12, -1], [1, -1], [1, 9], [32, -1], [33, -1], [34, 31], [35, -1], [36, 26], [37, -1], [38, -1], [39, -1], [40, -1], [41, -1], [42, 26], [0, -1], [44, -1], [45, 4], [40, -1], [47, -1], [36, 0], [49, -1], [-1, -1], [51, -1], [52, -1], [53, -1], [14, -1], [55, -1], [15, -1], [23, -1], [58, -1], [59, -1], [2, -1], [61, 59], [62, -1], [63, -1], [-1, -1], [65, -1], [66, -1], [67, -1], [68, -1], [37, 28], [69, 25], [71, -1], [72, -1], [50, 2], [74, -1], [12, -1], [18, -1], [77, -1], [78, -1], [79, -1], [43, 33], [81, -1], [82, -1], [83, -1], [84, 45], [85, -1], [86, -1], [-1, -1], [88, -1], [-1, -1], [76, 83], [44, -1], [92, -1], [93, -1], [9, -1], [95, 67], [96, -1], [97, -1], [-1, -1], ] problem_rev = 28 problem_base = 70 # problem_rev is a parent of problem_base, but a faulty implementation # could forget to remove it. bases = {60, 26, 70, 3, 96, 19, 98, 49, 97, 47, 1, 6} if problem_rev not in vecgraph[problem_base] or problem_base not in bases: print("Conditions have changed") missanc = ancestor.incrementalmissingancestors(vecgraph.__getitem__, bases) revs = {4, 12, 41, 28, 68, 38, 1, 30, 56, 44} missanc.removeancestorsfrom(revs) if 28 in revs: print("Failed!") else: print("Ok") def genlazyancestors(revs, stoprev=0, inclusive=False): print( ( "%% lazy ancestor set for %s, stoprev = %s, inclusive = %s" % (revs, stoprev, inclusive) ) ) return ancestor.lazyancestors( graph.get, revs, stoprev=stoprev, inclusive=inclusive ) def printlazyancestors(s, l): print('membership: %r' % [n for n in l if n in s]) print('iteration: %r' % list(s)) def test_lazyancestors(): # Empty revs s = genlazyancestors([]) printlazyancestors(s, [3, 0, -1]) # Standard example s = genlazyancestors([11, 13]) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) # Standard with ancestry in the initial set (1 is ancestor of 3) s = genlazyancestors([1, 3]) printlazyancestors(s, [1, -1, 0]) # Including revs s = genlazyancestors([11, 13], inclusive=True) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) # Test with stoprev s = genlazyancestors([11, 13], stoprev=6) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) s = genlazyancestors([11, 13], stoprev=6, inclusive=True) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) # Test with stoprev >= min(initrevs) s = genlazyancestors([11, 13], stoprev=11, inclusive=True) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) s = genlazyancestors([11, 13], stoprev=12, inclusive=True) printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0]) # Contiguous chains: 5->4, 2->1 (where 1 is in seen set), 1->0 s = genlazyancestors([10, 1], inclusive=True) printlazyancestors(s, [2, 10, 4, 5, -1, 0, 1]) # The C gca algorithm requires a real repo. These are textual descriptions of # DAGs that have been known to be problematic, and, optionally, known pairs # of revisions and their expected ancestor list. dagtests = [ (b'+2*2*2/*3/2', {}), (b'+3*3/*2*2/*4*4/*4/2*4/2*2', {}), (b'+2*2*/2*4*/4*/3*2/4', {(6, 7): [3, 5]}), ] def test_gca(): u = uimod.ui.load() for i, (dag, tests) in enumerate(dagtests): repo = hg.repository(u, b'gca%d' % i, create=1) cl = repo.changelog if not util.safehasattr(cl.index, 'ancestors'): # C version not available return debugcommands.debugbuilddag(u, repo, dag) # Compare the results of the Python and C versions. This does not # include choosing a winner when more than one gca exists -- we make # sure both return exactly the same set of gcas. # Also compare against expected results, if available. for a in cl: for b in cl: cgcas = sorted(cl.index.ancestors(a, b)) pygcas = sorted(ancestor.ancestors(cl.parentrevs, a, b)) expected = None if (a, b) in tests: expected = tests[(a, b)] if cgcas != pygcas or (expected and cgcas != expected): print( "test_gca: for dag %s, gcas for %d, %d:" % (dag, a, b) ) print(" C returned: %s" % cgcas) print(" Python returned: %s" % pygcas) if expected: print(" expected: %s" % expected) def main(): seed = None opts, args = getopt.getopt(sys.argv[1:], 's:', ['seed=']) for o, a in opts: if o in ('-s', '--seed'): seed = long(a, base=0) # accepts base 10 or 16 strings if seed is None: try: seed = long(binascii.hexlify(os.urandom(16)), 16) except AttributeError: seed = long(time.time() * 1000) rng = random.Random(seed) test_missingancestors_explicit() test_missingancestors(seed, rng) test_lazyancestors() test_gca() if __name__ == '__main__': main()