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