patch.diff: add support for diffs relative to a subdirectory
For now this implementation is pretty naive -- it filters out files right
before passing them into trydiff. In upcoming patches we'll add some more
smarts.
from mercurial import ancestor, commands, hg, ui, util
from mercurial.node import nullrev
import binascii, getopt, math, os, random, sys, time
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(range(0, p1) + 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] = set([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 >> sys.stderr, 'seed:', hex(seed)[:-1]
if gerrs[0] == 0:
print >> sys.stderr, 'graph:', graph
print >> sys.stderr, '* bases:', bases
print >> sys.stderr, '* seq: ', seq
print >> sys.stderr, '* output: ', output
print >> sys.stderr, '* expected:', expected
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 = []
revs = []
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: [0], 2: [1], 3: [1], 4: [2], 5: [4], 6: [4],
7: [4], 8: [-1], 9: [6, 7], 10: [5], 11: [3, 7], 12: [9],
13: [8]}
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])
# The C gca algorithm requires a real repo. These are textual descriptions of
# DAGs that have been known to be problematic.
dagtests = [
'+2*2*2/*3/2',
'+3*3/*2*2/*4*4/*4/2*4/2*2',
]
def test_gca():
u = ui.ui()
for i, dag in enumerate(dagtests):
repo = hg.repository(u, 'gca%d' % i, create=1)
cl = repo.changelog
if not util.safehasattr(cl.index, 'ancestors'):
# C version not available
return
commands.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.
for a in cl:
for b in cl:
cgcas = sorted(cl.index.ancestors(a, b))
pygcas = sorted(ancestor.ancestors(cl.parentrevs, a, b))
if cgcas != pygcas:
print "test_gca: for dag %s, gcas for %d, %d:" % (dag, a, b)
print " C returned: %s" % cgcas
print " Python returned: %s" % pygcas
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(seed, rng)
test_lazyancestors()
test_gca()
if __name__ == '__main__':
main()