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313 lines
12 KiB
313 lines
12 KiB
# -*- coding: utf-8 -*-
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# Copyright (C) 2012 Niels Thykier <niels@thykier.net>
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# - Includes code by Paul Harrison
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# (http://www.logarithmic.net/pfh-files/blog/01208083168/sort.py)
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version.
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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from __future__ import print_function
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import os
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from collections import deque
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from britney2.utils import (ifilter_only, iter_except)
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from britney2.installability.tester import InstallabilityTester
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class InstallabilitySolver(InstallabilityTester):
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def __init__(self, universe, revuniverse, testing, broken, essentials,
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safe_set, eqv_table):
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"""Create a new installability solver
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universe is a dict mapping package tuples to their
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dependencies and conflicts.
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revuniverse is a dict mapping package tuples to their reverse
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dependencies and reverse conflicts.
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testing is a (mutable) set of package tuples that determines
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which of the packages in universe are currently in testing.
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broken is a (mutable) set of package tuples that are known to
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be uninstallable.
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Package tuple: (pkg_name, pkg_version, pkg_arch)
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- NB: arch:all packages are "re-mapped" to given architecture.
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(simplifies caches and dependency checking)
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"""
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super().__init__(universe, revuniverse, testing,
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broken, essentials, safe_set, eqv_table)
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def solve_groups(self, groups):
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sat_in_testing = self._testing.isdisjoint
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universe = self._universe
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revuniverse = self._revuniverse
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result = []
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emitted = set()
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queue = deque()
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order = {}
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ptable = {}
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key2item = {}
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going_out = set()
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going_in = set()
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debug_solver = 0
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try: # pragma: no cover
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debug_solver = int(os.environ.get('BRITNEY_DEBUG', '0'))
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except:
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pass
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# Build the tables
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for (item, adds, rms) in groups:
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key = str(item)
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key2item[key] = item
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order[key] = {'before': set(), 'after': set()}
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going_in.update(adds)
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going_out.update(rms)
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for a in adds:
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ptable[a] = key
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for r in rms:
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ptable[r] = key
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if debug_solver > 1: # pragma: no cover
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self._dump_groups(groups)
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# This large loop will add ordering constrains on each "item"
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# that migrates based on various rules.
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for (item, adds, rms) in groups:
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key = str(item)
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oldcons = set()
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newcons = set()
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for r in rms:
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oldcons.update(universe[r][1])
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for a in adds:
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newcons.update(universe[a][1])
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current = newcons & oldcons
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oldcons -= current
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newcons -= current
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if oldcons:
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# Some of the old binaries have "conflicts" that will
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# be removed.
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for o in ifilter_only(ptable, oldcons):
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# "key" removes a conflict with one of
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# "other"'s binaries, so it is probably a good
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# idea to migrate "key" before "other"
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other = ptable[o]
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if other == key:
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# "Self-conflicts" => ignore
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continue
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if debug_solver and other not in order[key]['before']: # pragma: no cover
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print("N: Conflict induced order: %s before %s" % (key, other))
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order[key]['before'].add(other)
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order[other]['after'].add(key)
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for r in ifilter_only(revuniverse, rms):
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# The binaries have reverse dependencies in testing;
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# check if we can/should migrate them first.
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for rdep in revuniverse[r][0]:
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for depgroup in universe[rdep][0]:
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rigid = depgroup - going_out
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if not sat_in_testing(rigid):
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# (partly) satisfied by testing, assume it is okay
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continue
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if rdep in ptable:
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other = ptable[rdep]
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if other == key:
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# "Self-dependency" => ignore
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continue
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if debug_solver and other not in order[key]['after']: # pragma: no cover
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print("N: Removal induced order: %s before %s" % (key, other))
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order[key]['after'].add(other)
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order[other]['before'].add(key)
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for a in adds:
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# Check if this item should migrate before others
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# (e.g. because they depend on a new [version of a]
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# binary provided by this item).
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for depgroup in universe[a][0]:
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rigid = depgroup - going_out
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if not sat_in_testing(rigid):
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# (partly) satisfied by testing, assume it is okay
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continue
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# okay - we got three cases now.
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# - "swap" (replace existing binary with a newer version)
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# - "addition" (add new binary without removing any)
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# - "removal" (remove binary without providing a new)
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#
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# The problem is that only the two latter requires
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# an ordering. A "swap" (in itself) should not
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# affect us.
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other_adds = set()
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other_rms = set()
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for d in ifilter_only(ptable, depgroup):
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if d in going_in:
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# "other" provides something "key" needs,
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# schedule accordingly.
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other = ptable[d]
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other_adds.add(other)
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else:
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# "other" removes something "key" needs,
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# schedule accordingly.
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other = ptable[d]
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other_rms.add(other)
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for other in (other_adds - other_rms):
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if debug_solver and other != key and other not in order[key]['after']: # pragma: no cover
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print("N: Dependency induced order (add): %s before %s" % (key, other))
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order[key]['after'].add(other)
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order[other]['before'].add(key)
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for other in (other_rms - other_adds):
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if debug_solver and other != key and other not in order[key]['before']: # pragma: no cover
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print("N: Dependency induced order (remove): %s before %s" % (key, other))
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order[key]['before'].add(other)
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order[other]['after'].add(key)
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### MILESTONE: Partial-order constrains computed ###
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# At this point, we have computed all the partial-order
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# constrains needed. Some of these may have created strongly
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# connected components (SSC) [of size 2 or greater], which
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# represents a group of items that (we believe) must migrate
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# together.
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#
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# Each one of those components will become an "easy" hint.
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comps = self._compute_scc(order, ptable)
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merged = {}
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scc = {}
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# Now that we got the SSCs (in comps), we select on item from
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# each SSC to represent the group and become an ID for that
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# SSC.
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# * ssc[ssc_id] => All the items in that SSC
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# * merged[item] => The ID of the SSC to which the item belongs.
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#
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# We also "repair" the ordering, so we know in which order the
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# hints should be emitted.
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for com in comps:
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scc_id = com[0]
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scc[scc_id] = com
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merged[scc_id] = scc_id
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if len(com) > 1:
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so_before = order[scc_id]['before']
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so_after = order[scc_id]['after']
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for n in com:
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if n == scc_id:
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continue
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so_before.update(order[n]['before'])
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so_after.update(order[n]['after'])
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merged[n] = scc_id
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del order[n]
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if debug_solver: # pragma: no cover
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print("N: SCC: %s -- %s" % (scc_id, str(sorted(com))))
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for com in comps:
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node = com[0]
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nbefore = set(merged[b] for b in order[node]['before'])
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nafter = set(merged[b] for b in order[node]['after'])
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# Drop self-relations (usually caused by the merging)
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nbefore.discard(node)
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nafter.discard(node)
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order[node]['before'] = nbefore
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order[node]['after'] = nafter
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if debug_solver: # pragma: no cover
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print("N: -- PARTIAL ORDER --")
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initial_round = []
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for com in sorted(order):
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if debug_solver and order[com]['before']: # pragma: no cover
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print("N: %s <= %s" % (com, str(sorted(order[com]['before']))))
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if not order[com]['after']:
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# This component can be scheduled immediately, add it
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# to the queue
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initial_round.append(com)
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elif debug_solver: # pragma: no cover
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print("N: %s >= %s" % (com, str(sorted(order[com]['after']))))
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queue.extend(sorted(initial_round, key=len))
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del initial_round
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if debug_solver: # pragma: no cover
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print("N: -- END PARTIAL ORDER --")
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print("N: -- LINEARIZED ORDER --")
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for cur in iter_except(queue.popleft, IndexError):
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if order[cur]['after'] <= emitted and cur not in emitted:
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# This item is ready to be emitted right now
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if debug_solver: # pragma: no cover
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print("N: %s -- %s" % (cur, sorted(scc[cur])))
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emitted.add(cur)
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result.append([key2item[x] for x in scc[cur]])
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if order[cur]['before']:
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# There are components that come after this one.
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# Add it to queue:
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# - if it is ready, it will be emitted.
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# - else, it will be dropped and re-added later.
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queue.extend(sorted(order[cur]['before'] - emitted, key=len))
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if debug_solver: # pragma: no cover
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print("N: -- END LINEARIZED ORDER --")
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return result
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def _compute_scc(self, order, ptable):
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"""
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Tarjan's algorithm and topological sorting implementation in Python
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Find the strongly connected components in a graph using
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Tarjan's algorithm.
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by Paul Harrison
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Public domain, do with it as you will
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"""
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result = [ ]
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stack = [ ]
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low = { }
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def visit(node):
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if node in low:
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return
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num = len(low)
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low[node] = num
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stack_pos = len(stack)
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stack.append(node)
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for successor in order[node]['before']:
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visit(successor)
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low[node] = min(low[node], low[successor])
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if num == low[node]:
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component = tuple(stack[stack_pos:])
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del stack[stack_pos:]
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result.append(component)
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for item in component:
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low[item] = len(ptable)
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for node in order:
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visit(node)
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return result
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def _dump_groups(self, groups): # pragma: no cover
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print("N: === Groups ===")
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for (item, adds, rms) in groups:
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print("N: %s => A: %s, R: %s" % (str(item), str(adds), str(rms)))
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print("N: === END Groups ===")
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