202 lines
6.8 KiB
Python
202 lines
6.8 KiB
Python
# vim: tabstop=4 shiftwidth=4 softtabstop=4
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import collections
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import itertools
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from heat.common import exception
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class CircularDependencyException(exception.OpenstackException):
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message = _("Circular Dependency Found: %(cycle)s")
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class Dependencies(object):
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'''Helper class for calculating a dependency graph'''
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class Node(object):
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def __init__(self, requires=None, required_by=None):
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'''
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Initialise the node, optionally with a set of keys this node
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requires and/or a set of keys that this node is required by.
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'''
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self.require = requires and requires.copy() or set()
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self.satisfy = required_by and required_by.copy() or set()
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def copy(self):
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'''Make a copy of the node'''
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return Dependencies.Node(self.require, self.satisfy)
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def reverse_copy(self):
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'''Make a copy of the node with the edge directions reversed'''
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return Dependencies.Node(self.satisfy, self.require)
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def required_by(self, source=None):
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'''
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List the keys that require this node, and optionally add a
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new one
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'''
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if source is not None:
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self.satisfy.add(source)
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return iter(self.satisfy)
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def requires(self, target):
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'''Add a key that this node requires'''
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self.require.add(target)
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def __isub__(self, target):
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'''Remove a key that this node requires'''
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self.require.remove(target)
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return self
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def __nonzero__(self):
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'''Test if this node is a leaf (requires nothing)'''
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return bool(self.require)
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def stem(self):
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'''Test if this node is a stem (required by nothing)'''
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return not bool(self.satisfy)
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def disjoint(self):
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'''Test if this node is both a lead and a stem'''
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return self and self.stem()
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def __len__(self):
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'''Count the number of keys required by this node'''
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return len(self.require)
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def __iter__(self):
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'''Iterate over the keys required by this node'''
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return iter(self.require)
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def __str__(self):
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'''Return a human-readable string representation of the node'''
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return '{%s}' % ', '.join(str(n) for n in self)
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def __repr__(self):
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'''Return a string representation of the node'''
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return repr(self.require)
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def __init__(self, edges=[]):
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'''
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Initialise, optionally with a list of edges, in the form of
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(requirer, required) tuples.
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'''
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self.deps = collections.defaultdict(self.Node)
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for e in edges:
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self += e
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def __iadd__(self, edge):
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'''Add another edge, in the form of a (requirer, required) tuple'''
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requirer, required = edge
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if required is None:
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# Just ensure the node is created by accessing the defaultdict
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self.deps[requirer]
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else:
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self.deps[required].required_by(requirer)
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self.deps[requirer].requires(required)
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return self
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def __getitem__(self, last):
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'''
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Return a partial dependency graph consisting of the specified node and
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all those that require it only.
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'''
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if last not in self.deps:
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raise KeyError
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def get_edges(key):
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def requirer_edges(rqr):
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# Concatenate the dependency on the current node with the
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# recursive generated list
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return itertools.chain([(rqr, key)], get_edges(rqr))
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# Get the edge list for each node that requires the current node
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edge_lists = itertools.imap(requirer_edges,
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self.deps[key].required_by())
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# Combine the lists into one long list
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return itertools.chain.from_iterable(edge_lists)
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if self.deps[last].stem():
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# Nothing requires this, so just add the node itself
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edges = [(last, None)]
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else:
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edges = get_edges(last)
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return Dependencies(edges)
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@staticmethod
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def _deps_to_str(deps):
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'''Convert the given dependency graph to a human-readable string'''
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pairs = ('%s: %s' % (str(k), str(v)) for k, v in deps.items())
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return '{%s}' % ', '.join(pairs)
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def __str__(self):
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'''
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Return a human-readable string representation of the dependency graph
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'''
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return self._deps_to_str(self.deps)
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def _edges(self):
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'''Return an iterator over all of the edges in the graph'''
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def outgoing_edges(rqr, node):
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if node.disjoint():
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yield (rqr, None)
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else:
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for rqd in node:
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yield (rqr, rqd)
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return (outgoing_edges(*item) for item in self.deps.iteritems())
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def __repr__(self):
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'''Return a string representation of the object'''
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return 'Dependencies([%s])' % ', '.join(repr(e) for e in edges)
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def _toposort(self, deps):
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'''Generate a topological sort of a dependency graph'''
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def next_leaf():
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for leaf, node in deps.items():
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if not node:
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return leaf, node
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# There are nodes remaining, but no more leaves: a cycle
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cycle = self._deps_to_str(deps)
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raise CircularDependencyException(cycle=cycle)
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for iteration in xrange(len(deps)):
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leaf, node = next_leaf()
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yield leaf
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# Remove the node and all edges connected to it before continuing
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# to look for more leaves
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for src in node.required_by():
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deps[src] -= leaf
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del deps[leaf]
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def _mapgraph(self, func):
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'''Map the supplied function onto every node in the graph.'''
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return dict((k, func(n)) for k, n in self.deps.items())
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def __iter__(self):
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'''Return a topologically sorted iterator'''
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deps = self._mapgraph(lambda n: n.copy())
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return self._toposort(deps)
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def __reversed__(self):
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'''Return a reverse topologically sorted iterator'''
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rev_deps = self._mapgraph(lambda n: n.reverse_copy())
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return self._toposort(rev_deps)
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