Mercurial > hg
view tests/test-ancestor.py @ 48598:a6f16ec07ed7
stream-clone: add a explicit test for format change during stream clone
They are different kind of requirements, the one which impact the data storage
and are relevant to the files being streamed and the one which does not. For
example some requirements are only relevant to the working copy, like sparse, or
dirstate-v2.
Since they are irrelevant to the content being streamed, they do not prevent the
receiving side to use streaming clone and mercurial skip adverting them over
the wire and, ideally, within the bundle.
In addition, this let the client decide to use whichever format it desire for
the part that does not affect the store itself. So the configuration related to
these format are used as normal when doing a streaming clone.
In practice, the feature was not really tested and is badly broken with bundle-2,
since the requirements are not filtered out from the stream bundle.
So we start with adding simple tests as a good base before the fix and adjust
the feature.
Differential Revision: https://phab.mercurial-scm.org/D12029
author | Pierre-Yves David <pierre-yves.david@octobus.net> |
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date | Mon, 17 Jan 2022 18:51:47 +0100 |
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()