bundle2: support for bundling and unbundling payload
We add the ability to bundle and unbundle a payload in parts. The payload is the
actual binary data of the part. It is used to convey all the applicative data.
For now we stick to very simple implementation with all the data fit in single
chunk. This open the door to some bundle2 testing usage. This will be improved before
bundle2 get used for real. We need to be able to stream the payload in multiple
part to exchange any changegroup efficiently. This simple version will do for
now.
Bundling and unbundling are done in the same changeset because the test for
parts is less modular. However, the result is not too complex.
# ancestor.py - generic DAG ancestor algorithm for mercurial
#
# Copyright 2006 Matt Mackall <mpm@selenic.com>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.
import heapq
import util
from node import nullrev
def ancestors(pfunc, *orignodes):
"""
Returns the common ancestors of a and b that are furthest from a
root (as measured by longest path).
pfunc must return a list of parent vertices for a given vertex.
"""
if not isinstance(orignodes, set):
orignodes = set(orignodes)
if nullrev in orignodes:
return set()
if len(orignodes) <= 1:
return orignodes
def candidates(nodes):
allseen = (1 << len(nodes)) - 1
seen = [0] * (max(nodes) + 1)
for i, n in enumerate(nodes):
seen[n] = 1 << i
poison = 1 << (i + 1)
gca = set()
interesting = len(nodes)
nv = len(seen) - 1
while nv >= 0 and interesting:
v = nv
nv -= 1
if not seen[v]:
continue
sv = seen[v]
if sv < poison:
interesting -= 1
if sv == allseen:
gca.add(v)
sv |= poison
if v in nodes:
# history is linear
return set([v])
if sv < poison:
for p in pfunc(v):
sp = seen[p]
if p == nullrev:
continue
if sp == 0:
seen[p] = sv
interesting += 1
elif sp != sv:
seen[p] |= sv
else:
for p in pfunc(v):
if p == nullrev:
continue
sp = seen[p]
if sp and sp < poison:
interesting -= 1
seen[p] = sv
return gca
def deepest(nodes):
interesting = {}
count = max(nodes) + 1
depth = [0] * count
seen = [0] * count
mapping = []
for (i, n) in enumerate(sorted(nodes)):
depth[n] = 1
b = 1 << i
seen[n] = b
interesting[b] = 1
mapping.append((b, n))
nv = count - 1
while nv >= 0 and len(interesting) > 1:
v = nv
nv -= 1
dv = depth[v]
if dv == 0:
continue
sv = seen[v]
for p in pfunc(v):
if p == nullrev:
continue
dp = depth[p]
nsp = sp = seen[p]
if dp <= dv:
depth[p] = dv + 1
if sp != sv:
interesting[sv] += 1
nsp = seen[p] = sv
if sp:
interesting[sp] -= 1
if interesting[sp] == 0:
del interesting[sp]
elif dv == dp - 1:
nsp = sp | sv
if nsp == sp:
continue
seen[p] = nsp
interesting.setdefault(nsp, 0)
interesting[nsp] += 1
interesting[sp] -= 1
if interesting[sp] == 0:
del interesting[sp]
interesting[sv] -= 1
if interesting[sv] == 0:
del interesting[sv]
if len(interesting) != 1:
return []
k = 0
for i in interesting:
k |= i
return set(n for (i, n) in mapping if k & i)
gca = candidates(orignodes)
if len(gca) <= 1:
return gca
return deepest(gca)
def genericancestor(a, b, pfunc):
"""
Returns the common ancestor of a and b that is furthest from a
root (as measured by longest path) or None if no ancestor is
found. If there are multiple common ancestors at the same
distance, the first one found is returned.
pfunc must return a list of parent vertices for a given vertex
"""
if a == b:
return a
a, b = sorted([a, b])
# find depth from root of all ancestors
# depth is stored as a negative for heapq
parentcache = {}
visit = [a, b]
depth = {}
while visit:
vertex = visit[-1]
pl = [p for p in pfunc(vertex) if p != nullrev]
parentcache[vertex] = pl
if not pl:
depth[vertex] = 0
visit.pop()
else:
for p in pl:
if p == a or p == b: # did we find a or b as a parent?
return p # we're done
if p not in depth:
visit.append(p)
if visit[-1] == vertex:
# -(maximum distance of parents + 1)
depth[vertex] = min([depth[p] for p in pl]) - 1
visit.pop()
# traverse ancestors in order of decreasing distance from root
def ancestors(vertex):
h = [(depth[vertex], vertex)]
seen = set()
while h:
d, n = heapq.heappop(h)
if n not in seen:
seen.add(n)
yield (d, n)
for p in parentcache[n]:
heapq.heappush(h, (depth[p], p))
def generations(vertex):
sg, s = None, set()
for g, v in ancestors(vertex):
if g != sg:
if sg:
yield sg, s
sg, s = g, set((v,))
else:
s.add(v)
yield sg, s
x = generations(a)
y = generations(b)
gx = x.next()
gy = y.next()
# increment each ancestor list until it is closer to root than
# the other, or they match
try:
while True:
if gx[0] == gy[0]:
for v in gx[1]:
if v in gy[1]:
return v
gy = y.next()
gx = x.next()
elif gx[0] > gy[0]:
gy = y.next()
else:
gx = x.next()
except StopIteration:
return None
def missingancestors(revs, bases, pfunc):
"""Return all the ancestors of revs that are not ancestors of bases.
This may include elements from revs.
Equivalent to the revset (::revs - ::bases). Revs are returned in
revision number order, which is a topological order.
revs and bases should both be iterables. pfunc must return a list of
parent revs for a given revs.
"""
revsvisit = set(revs)
basesvisit = set(bases)
if not revsvisit:
return []
if not basesvisit:
basesvisit.add(nullrev)
start = max(max(revsvisit), max(basesvisit))
bothvisit = revsvisit.intersection(basesvisit)
revsvisit.difference_update(bothvisit)
basesvisit.difference_update(bothvisit)
# At this point, we hold the invariants that:
# - revsvisit is the set of nodes we know are an ancestor of at least one
# of the nodes in revs
# - basesvisit is the same for bases
# - bothvisit is the set of nodes we know are ancestors of at least one of
# the nodes in revs and one of the nodes in bases
# - a node may be in none or one, but not more, of revsvisit, basesvisit
# and bothvisit at any given time
# Now we walk down in reverse topo order, adding parents of nodes already
# visited to the sets while maintaining the invariants. When a node is
# found in both revsvisit and basesvisit, it is removed from them and
# added to bothvisit instead. When revsvisit becomes empty, there are no
# more ancestors of revs that aren't also ancestors of bases, so exit.
missing = []
for curr in xrange(start, nullrev, -1):
if not revsvisit:
break
if curr in bothvisit:
bothvisit.remove(curr)
# curr's parents might have made it into revsvisit or basesvisit
# through another path
for p in pfunc(curr):
revsvisit.discard(p)
basesvisit.discard(p)
bothvisit.add(p)
continue
# curr will never be in both revsvisit and basesvisit, since if it
# were it'd have been pushed to bothvisit
if curr in revsvisit:
missing.append(curr)
thisvisit = revsvisit
othervisit = basesvisit
elif curr in basesvisit:
thisvisit = basesvisit
othervisit = revsvisit
else:
# not an ancestor of revs or bases: ignore
continue
thisvisit.remove(curr)
for p in pfunc(curr):
if p == nullrev:
pass
elif p in othervisit or p in bothvisit:
# p is implicitly in thisvisit. This means p is or should be
# in bothvisit
revsvisit.discard(p)
basesvisit.discard(p)
bothvisit.add(p)
else:
# visit later
thisvisit.add(p)
missing.reverse()
return missing
class lazyancestors(object):
def __init__(self, cl, revs, stoprev=0, inclusive=False):
"""Create a new object generating ancestors for the given revs. Does
not generate revs lower than stoprev.
This is computed lazily starting from revs. The object supports
iteration and membership.
cl should be a changelog and revs should be an iterable. inclusive is
a boolean that indicates whether revs should be included. Revs lower
than stoprev will not be generated.
Result does not include the null revision."""
self._parentrevs = cl.parentrevs
self._initrevs = revs
self._stoprev = stoprev
self._inclusive = inclusive
# Initialize data structures for __contains__.
# For __contains__, we use a heap rather than a deque because
# (a) it minimizes the number of parentrevs calls made
# (b) it makes the loop termination condition obvious
# Python's heap is a min-heap. Multiply all values by -1 to convert it
# into a max-heap.
self._containsvisit = [-rev for rev in revs]
heapq.heapify(self._containsvisit)
if inclusive:
self._containsseen = set(revs)
else:
self._containsseen = set()
def __iter__(self):
"""Generate the ancestors of _initrevs in reverse topological order.
If inclusive is False, yield a sequence of revision numbers starting
with the parents of each revision in revs, i.e., each revision is *not*
considered an ancestor of itself. Results are in breadth-first order:
parents of each rev in revs, then parents of those, etc.
If inclusive is True, yield all the revs first (ignoring stoprev),
then yield all the ancestors of revs as when inclusive is False.
If an element in revs is an ancestor of a different rev it is not
yielded again."""
seen = set()
revs = self._initrevs
if self._inclusive:
for rev in revs:
yield rev
seen.update(revs)
parentrevs = self._parentrevs
stoprev = self._stoprev
visit = util.deque(revs)
while visit:
for parent in parentrevs(visit.popleft()):
if parent >= stoprev and parent not in seen:
visit.append(parent)
seen.add(parent)
yield parent
def __contains__(self, target):
"""Test whether target is an ancestor of self._initrevs."""
# Trying to do both __iter__ and __contains__ using the same visit
# heap and seen set is complex enough that it slows down both. Keep
# them separate.
seen = self._containsseen
if target in seen:
return True
parentrevs = self._parentrevs
visit = self._containsvisit
stoprev = self._stoprev
heappop = heapq.heappop
heappush = heapq.heappush
targetseen = False
while visit and -visit[0] > target and not targetseen:
for parent in parentrevs(-heappop(visit)):
if parent < stoprev or parent in seen:
continue
# We need to make sure we push all parents into the heap so
# that we leave it in a consistent state for future calls.
heappush(visit, -parent)
seen.add(parent)
if parent == target:
targetseen = True
return targetseen