#!/usr/bin/env python

'''Directed and undirected graph data structures and algorithms.

Copyright 2004, Robert Dick (dickrp@ece.northwestern.edu).
Please see the license at the end of the source code for legal information.'''

__version__ = '0.2'
__author__ = 'Robert Dick (dickrp@ece.northwestern.edu)'


import copy, new, operator, struct, delegate

# The following four lines borrowed from Gregory R. Warnes's fpconst
# (until it's standard in Python distributions).
if struct.pack('i',1)[0] != '\x01':
    PosInf = struct.unpack('d', '\x7F\xF0\x00\x00\x00\x00\x00\x00')[0]
else:
    PosInf = struct.unpack('d', '\x00\x00\x00\x00\x00\x00\xf0\x7f')[0]


class GraphError(StandardError):
            '''Exception for graph errors.'''
            pass


class SortStruct(float, object):
            '''Throw-away class for temporarily holding values.

            Initialize with a float distance and as many keyword args as desired.
            The keyword args become attributes.'''

            def __new__(cls, val, **kargs):
                    obj = float.__new__(cls, val)
                    obj.__dict__ = kargs
                    return obj

            @property
            def number(self): return float(self)


def _condop(cond, v1, v2):
            if cond:
                    return v1
            else:
                    return v2

def _roprop(description = None):
            def prop_func(ro_method):
                    return property(ro_method, None, None, description)
            return prop_func

#================================================================================

class Vertex(delegate.Delegate):
            '''General graph vertex.

            All methods colaborate with directed and undirected
            edges.  If the edges are undirected, ine == oute.

            Variables :
            --------------------
                self._e = list of edges of this vertex
                self.in_e = list of incoming edges (decorator)
                self.out_e = list of outgoing edges (decorator)
                self.all_e = list of all edges = self._e (decorator)

            '''

            def attach_e(self, e):
                    '''Attach an edge.'''
                    self._e.append(e)

            def connecting_e(self, v):
                    '''List of edges connecting self and other vertex.'''
                    return [e for e in self._e if e.leaves(self) and e.enters(v)]

            def __init__(self, name):
                    '''Name neen't be a string but must be hashable and immutable.'''
                    self.__Delegate.__init__(self)
                    self._e = []
                    self.name = name

            def __str__(self): return str(self.name)

            def __getstate__(self):
                    '''Need to break cycles to prevent recursion blowup in pickle.

                    Dump everything except for edges.'''
                    dcp = copy.copy(self.__dict__)
                    dcp['_e'] = []
                    return dcp

            @_roprop('All edges.')
            def all_e(self): return self._e

            @_roprop('Incoming edges.')
            def in_e(self): return [e for e in self._e if e.enters(self)]

            @_roprop('Outgoing edges.')
            def out_e(self): return [e for e in self._e if e.leaves(self)]

            @_roprop('Set of adjacent vertices.  Edge direction ignored.')
            def adjacent_v(self):
                    adj = set(v for e in self._e for v in e.all_v)
                    try: adj.remove(self)
                    except: pass
                    return adj

            @_roprop('Set of vertices connected by incoming edges.')
            def in_v(self):
                    return set(v for e in self._e for v in e.src_v if e.enters(self))

            @_roprop('Set of vertices connected by outgoing edges.')
            def out_v(self):
                    return set(v for e in self._e for v in e.dest_v if e.leaves(self))

            @_roprop('True if vertex has no outgoing edges.')
            def is_sink(self): return not self.out_e

            @_roprop('True if vertex has no incoming edges.')
            def is_src(self): return not self.in_e

            @_roprop('True if vertex has incoming and outgoing edges.')
            def is_intermed(self): return not self.is_sink and not self.is_src

            def __eq__(a,b):
                return hash(a) == hash(b)

#===========================================================================

class RawEdge(delegate.Delegate):
            '''Base class for undirected and directed edges.  Not directly useful.'''

            def __init__(self, name, v1, v2):
                    '''Name needn't be a string but must be immutable and hashable.'''
                    self.__Delegate.__init__(self)
                    self.name = name
                    self._v = [v1, v2]
                    v1.attach_e(self)
                    v2.attach_e(self)

            def __setstate__(self, state):
                    '''Restore own state and add self to connected vertex edge lists.'''
                    self.__dict__ = state
                    self._v[0].attach_e(self)
                    self._v[1].attach_e(self)

            @_roprop('All connected vertices.')
            def all_v(self): return self._v


class UndirEdge(RawEdge):
            '''Undirected edge.'''

            def enters(self, v):
                    '''True if this edge is connected to the vertex.'''
                    return v in self._v

            def leaves(self, v):
                    '''True if this edge is connected to the vertex.'''
                    return v in self._v

            def __str__(self):
                    return '%s: %s -- %s' % (str(self.name), str(self._v[0]),
                                str(self._v[1]))

            def weight(self, v1, v2):
                    '''1 if this edge connects the vertices.'''
                    if v1 not in self._v or v2 not in self._v:
                                raise GraphError('vertices not connected')
                    return 1

            @_roprop('Source vertices.')
            def src_v(self): return self._v

            @_roprop('Destination vertices.')
            def dest_v(self): return self._v


class DirEdge(RawEdge):
            '''Directed edge.

                Variables :
                --------------
                self._v[0] = source vertex
                self._v[1] = destination vertex
            '''

            def enters(self, v):
                    '''True only if the vertex is this edge's destination.'''
                    return v is self._v[1]

            def leaves(self, v):
                    '''True only if the vertex is this edge's source.'''
                    return v is self._v[0]

            def invert(self):
                    '''Inverts the edge direction.'''
                    self._v.reverse()

            def weight(self, v1, v2):
                    '''1 if this edge has v1 as its source and v2 as its destination.'''
                    if v1 is not self._v[0] or v2 is not self._v[1]:
                                raise GraphError('vertices not connected')
                    return 1

            def __str__(self):
                    return '%s: %s -> %s' % (str(self.name), str(self._v[0]),
                                str(self._v[1]))

            @_roprop(
                    '''Single element list containing the edge's source vertex.

                    Must be a list to conform with UndirEdge's interface.''')
            def src_v(self): return [self._v[0]]

            @_roprop(
                    '''Single element list containing the edge's destination vertex.

                    Must be a list to conform with UndirEdge's interface.''')
            def dest_v(self): return [self._v[1]]

#================================================================================

def DataWrapped(cls):
            '''Returns a wrapped class with a new 'data' member.'''

            class __Wr(cls):
                    '''Wrapper to add 'data' to another class.'''

                    def __init__(self, *pargs, **kargs):
                                '''Use last parg for data and sends all other args to base.'''
                                if kargs:
                                            cls.__init__(self, *pargs[:-1], **kargs)
                                else:
                                            cls.__init__(self, *pargs[:-1])
                                self.data = pargs[-1]

                    def __str__(self):
                                '''Append data to base's __str__.'''
                                return ' '.join(filter(None, (cls.__str__(self), str(self.data))))

            __Wr.__name__ = 'Data%s' % cls.__name__.split('.')[-1]
            return __Wr

DataVertex = DataWrapped(Vertex)
DataUndirEdge = DataWrapped(UndirEdge)
DataDirEdge = DataWrapped(DirEdge)

#================================================================================

class VertexDict(dict, delegate.Delegate):
            '''Dictionary of vertices.'''

            def __init__(self, graph):
                    self.__dict.__init__(self)
                    self.__Delegate.__init__(self)
                    self.graph = graph

            def __setitem__(self, key, val):
                    if self.has_key(key):
                                raise KeyError('VertexDict already has (%s, %s).' % (key, val))
                    self.__dict.__setitem__(self, key, val)

            def __delitem__(self, key):
                    '''Delete all edges connected to the vertex, along with the vertex.'''
                    v = self[key]
                    for e in reversed(v._e):
                                del self.graph.e[e.name]
                    self.__dict.__delitem__(self, key)


class EdgeDict(dict, delegate.Delegate):
            '''Dictionary of edges.'''

            def __setitem__(self, key, val):
                    if self.has_key(key):
                                raise KeyError('EdgeDict already has (%s, %s).' % (key, val))
                    self.__dict.__setitem__(self, key, val)

            def __delitem__(self, key):
                    '''Remove edge from vertices to which it is attached.'''
                    e = self[key]
                    for v in e._v:
                                v._e.remove(e)
                    self.__dict.__delitem__(self, key)

#================================================================================

class Graph(delegate.Delegate):
            '''General-purpose graph data structure.'''

            def __init__(self, name = None):
                    self.name = name
                    self.v = VertexDict(self)
                    self.e = EdgeDict()

            def __str__(self):
                    return self.__class__.__name__ + \
                                _condop(self.name, ' ' + str(self.name), '') + '\nVertices:\n' + \
                                '\n'.join([str(v) for v in self.v.values()]) + \
                                '\n\nEdges:\n' + \
                                '\n'.join([str(e) for e in self.e.values()]) + '\n'




            @_roprop('List of all vertices.')
            def all_v(self): return [v for n, v in self.v.items()]

            @_roprop('List of all vertices without incoming edges.')
            def src_v(self): return [v for n, v in self.v.items() if v.is_src]

            @_roprop('List of all vertices without outgoing edges.')
            def sink_v(self): return [v for n, v in self.v.items() if v.is_sink]

            @_roprop(
                    'List of all vertices with both incoming and outgoing edges.')
            def intermed_v(self):   return [v for n, v in self.v.items() if v.is_intermed]

            def add_v(self, v):
                    '''Add and return a vertex.'''
                    self.v[v.name] = v
                    return v

            def add_e(self, e):
                    '''Add and return an edge.'''
                    self.e[e.name] = e
                    return e

            def del_e(self, e):
                    '''delete an edge (e is the name of the edge)'''
                    assert(self.e.has_key(e)), "The edge is not in the BNet"
                    del self.e[e]

            def connex_components(self):
                """ returns a list of list of nodes that are connected between
                 them"""
                unchecked = set(self.v.values())
                groups = []
                while len(unchecked):
                            vcon = self.member_family(unchecked.pop())
                            unchecked -= set(vcon)
                            groups.append(set(vcon))
                return groups
                    
            def member_family(self, node):
                unprocessed = [node]
                visited = []
                while unprocessed:
                            v = unprocessed.pop()
                            if v not in visited:
                                        visited.append(v)
                                        unprocessed.extend(v.out_v)
                                        unprocessed.extend(v.in_v)
                return visited                

            def connected_components(self):
                    '''Return a list of lists.  Each holds transitively-connected vertices.'''
                    unchecked = set(self.v.values())
                    groups = []
                    while len(unchecked):
                                vcon = self.depth_first_search(unchecked.pop())
                                unchecked -= set(vcon)
                                groups.append(vcon)
                    return groups

            @staticmethod
            def depth_first_search(start_v):
                    '''Return a depth-first search list of vertices.'''
                    unprocessed = [start_v]
                    visited = []
                    while unprocessed:
                                v = unprocessed.pop()
                                if v not in visited:
                                            visited.append(v)
                                            unprocessed.extend(v.out_v)
                    return visited

            @staticmethod
            def breadth_first_search(start_v):
                    '''Return a breadth-first search list of vertices.'''
                    unprocessed = [start_v]
                    visited = []
                    while unprocessed:
                                v = unprocessed.pop(0)
                                if v not in visited:
                                            visited.append(v)
                                            unprocessed.extend(v.out_v)
                    return visited

            #@staticmethod
            def topological_sort(self):
                '''Return a topological sort list of vertices.'''
                # unprocessed is a list of all nodes that have no parents
                unprocessed = [v for v in self.v.values() if not v.in_v]
                
                return Graph.topological_sort_by_node(unprocessed)

            @staticmethod
            def topological_sort_by_node(start_v):
                '''Return a topological sort list of vertices.'''
                unprocessed = start_v
                visited = []
                while unprocessed:
                    v = unprocessed.pop(0)
                    incoming_v = v.adjacent_v - v.out_v
                    if v not in visited and not (incoming_v - set(visited)):
                        visited.append(v)
                        unprocessed.extend(v.out_v)
                return visited

            def HasNoCycles(self, start_v):
                ''' Return True if the node start_v is not in a cycle
                '''
                unprocessed = [start_v]
                visited = []
                result = True
                i = 0
                while unprocessed:
                            i += 1
                            v = unprocessed.pop(0)
                            if i ==1:
                                unprocessed.extend(v.out_v)
                            elif start_v in visited:
                                result = False
                                break
                            elif v not in visited:
                                visited.append(v)
                                unprocessed.extend(v.out_v)
                return result

##            def HasNoCycles(self, start_v):
##                ''' Return True if the node start_v is not in a cycle
##                '''
##                unprocessed = [start_v]
##                visited = []
##                result = True
##                i = 0
##                while unprocessed:
##                            i += 1
##                            v = unprocessed.pop(0)
##                            if v not in visited:
##                                visited.append(v)
##                                unprocessed.extend(v.out_v)
##                            else:
##                                result = False
##                                break
##                return result

#================================================================================

            def minimal_span_tree(self, **kargs):
                    '''Return minimal spanning 'Tree'.

                    Keyword arg 'weight_func' is a function taking (edge, v1, v2) and
                    returning a weight.  Defaults to e.weight().
                    'targets' list of target vertices.  Defaults to all vertices.'''

                    def def_weight_func(e, v1, v2): return e.weight(v1, v2)
                    weight_func = kargs.get('weight_func', def_weight_func)
                    targets = kargs.get('targets', self.v.values())
                    visited = set([targets.pop()])
                    unvisited = set(self.v.values()) - visited
                    mst = Tree()

                    while targets:
# Haven't found it yet.  Search more.
                                connected = []
                                for v in visited:
                                            for u in unvisited:
                                                    conn = v.connecting_e(u)
                                                    if conn:
                                                                dist = weight_func(conn.pop(), v, u)
                                                                connected.append(SortStruct(dist, src=v, dest=u))

                                if not connected:
                                            raise GraphError('unreachable vertices in minimal_spanning_tree')

# Connect it
                                near = min(connected)
                                if near.src.name not in mst.v:
                                            mst.add_v(DataVertex(near.src.name, near.src))
                                if near.dest.name not in mst.v:
                                            mst.add_v(DataVertex(near.dest.name, near.src))
                                e = mst.auto_add_e(DirEdge(len(mst.e), mst.v[near.src.name],
                                            mst.v[near.dest.name]))

                                visited.add(near.dest)
                                unvisited.remove(near.dest)
                                targets.remove(near.dest)
                    return mst

#================================================================================

            def shortest_tree(self, start, **kargs):
                    '''Return a 'Tree' of shortest paths to all nodes.

                    Keyword arg 'weight_func' is a function taking (edge, v1, v2) and
                    returning a weight.  Defaults to e.weight().
                    'targets' list of target vertices.  Defaults to all vertices.'''

                    def def_weight_func(e, v1, v2): return e.weight(v1, v2)
                    weight_func = kargs.get('weight_func', def_weight_func)
                    targets = set(kargs.get('targets', self.v.values()))
                    path_tr = Tree()
                    dist = {start:0.0}
                    unvisited = set(self.v.values())
                    while targets:
# Determine the closest vertex
                                closest = min([(dist.get(v, PosInf), v) for v in unvisited])[1]
# Add it and push the distances
                                unvisited.remove(closest)
                                targets.discard(closest)
                                adj_v = closest.out_v
                                if not adj_v - unvisited:
                                            raise GraphError('unreachable vertices in shortest_tree')
                                for v in adj_v:
                                            for e in closest.connecting_e(v):
                                                    push_dist = weight_func(e, closest, v) + dist[closest]
                                                    if push_dist < dist.get(v, PosInf):
                                                                dist[v] = push_dist
# Add the vertices.  Remove the old edges, if any.  Add the new edge.
                                                                if closest.name not in path_tr.v:
                                                                            path_tr.add_v(DataVertex(closest.name, closest))
                                                                if v.name not in path_tr.v:
                                                                            path_tr.add_v(DataVertex(v.name, v))
                                                                e_nm = len(path_tr.e)
                                                                for e2 in path_tr.v[v.name].in_e:
                                                                            del path_tr.e[e2.name]
                                                                            e_nm = e2.name
                                                                path_tr.auto_add_e(DirEdge(e_nm, path_tr.v[closest.name],
                                                                            path_tr.v[v.name]))
                    return path_tr

#================================================================================

            def greedy_paths(self, start, goal, weight_func = None):
                    '''Return a dict of greedy paths with (start vertex, end vertex) keys.

                    Always makes the highest-gain decision.  Will find a path if one exists.
                    Not necessarily optimal.  'weight_func' is a function of (edge, v1, v2)
                    returning a weight.  Defaults to e.weight()'''

                    def def_weight_func(e, v1, v2): return e.weight(v1, v2)
                    weight_func = weight_func or def_weight_func
                    path = [start]
                    visited = set([start])
                    while path[-1] is not goal:
                                adj_v = [SortStruct(weight_func(e, path[-1], v), dest=v)
                                            for e in path[-1].out_e for v in e.dest_v if v not in visited]
                                if adj_v:
                                            closest_v = min(adj_v).dest
                                            visited.add(closest_v)
                                            path.append(closest_v)
                                else:
                                            path.pop()
# Prepare the dict
                    d = {}
                    for i1 in range(len(path)):
                                for i2 in range(i1, len(path)):
                                            d[path[i1], path[i2]] = path[i1:i2 + 1]
                    return d

            def all_pairs_sp(self, weight_func = None):
                    '''Return a dictionary of shortest path lists for all vertex pairs.

                    Keys are (source, destination) tuples.
                    'weight_func' is a function taking (edge, v1, v2) that returns a weight.
                    Defaults to e.weight()'''

                    return dict(self.shortest_tree(v,
                                weight_func=weight_func).path_dict().items() for v in self.v.values())

#================================================================================

            @staticmethod
            def path_weight(path, weight_func = None):
                    '''Return the weight of the path, which is a list of vertices.

                    'weight_func' is a function taking (edge, v1, v2) and returning a weight.'''

                    def def_weight_func(e, v1, v2): return e.weight(v1, v2)
                    weight_func = weight_func or def_weight_func
                    wt = 0.0
                    for v1, v2 in zip(path[:-1], path[1:]):
                                connect_e = [e for e in v1.out_e if e.enters(v2)]
                                if not connect_e:
                                            raise GraphError('vertices in path are not connected')
                                wt += min(weight_func(e, v1, v2) for e in connect_e)
                    return wt

#================================================================================
#================================================================================
#                   MY CODE !!!!!!!!!!!!!!! (Kostas Gaitanis)
#================================================================================
#================================================================================




class TreeError(GraphError): pass

class Tree(Graph):
            '''Tree data structure.

            Edges must be directed and reconvergent paths do not occur.'''

            def add_e(self, e):
                    '''Add edge if tree invariant holds.  Otherwise, raise exception.'''
                    if len(e.dest_v) != 1:
                                raise TreeError('undirected edge')
                    if len(e.dest_v[0].in_e) != 1:
                                raise TreeError('edge introduces reconvergent paths into tree')
                    return self.__Graph.add_e(self, e)

            def auto_add_e(self, e):
                    '''Automatically choose correct direction for new edge.'''
                    if len(e.dest_v) != 1:
                                raise TreeError('undirected edge')
                    if len(e.dest_v[0].in_e) != 1:
                                e.invert()
                    self.add_e(e)

            def is_safe_e(self, target_v):
                    '''True if edge maintains tree invariant.'''
                    return not target_v.in_e

            def path_dict(self):
                    '''Return a dictionary of path lists from the root to each vertex.

                    Keys are (source vertex, destination vertex) tuples.'''

                    root = self.src_v
                    assert len(root) == 1
                    root = root.pop()

                    d = {(root.data, root.data):[root.data]}
                    for v in self.depth_first_search(root):
                                parent = v.in_v
                                assert len(parent) <= 1
                                if parent:
                                            parent = parent.pop()
                                            d[root.data, v.data] = d[root.data, parent.data] + [v.data]
                    return d

#################################################################################
if __name__ == '__main__':
            G = Graph()
            a, b, c, d, e, f, g = [G.add_v(BVertex(nm)) for nm in 'a b c d e f g'.split()]
            for ep in [(a, b), (a, c), (b, d), (b, f), (b, e), (c, e), (d, f), (e, f),
            (f, g)]:
                    G.add_e(UndirEdge(len(G.e), *ep))

            print G
            #print 'DFS:', map(str, G.depth_first_search(a))
            #print 'BFS:', map(str, G.breadth_first_search(a))
            #print 'top sort:', map(str, G.topological_sort(a))

            #T = G.minimal_span_tree()
            #print T
            #print [(map(str, k), map(str, v)) for k, v in T.path_dict().items()]

            #S = G.shortest_tree(a)
            #print S

            print a



            ###################################################################
            # just in case, this is the copy method I created, but don't seem to need it
            ######################################
            def __copy__(self):
                    g = Graph('Copy of ' + str(self.name))

                    # copy vertices
                    for v in self.v.values():
                                if v.__class__.__name__ == 'BVertex':
                                            g.add_v(BVertex(v.name, v.nvalues))
                                elif v.__class__.__name__ == 'Vertex':
                                            g.add_v(Vertex(v.name))


                    # for each edge, create a corresponding edge in g
                    for e in self.e.values():
                                print e
                                print e._v[0].name
                                v1 = g.v[e._v[0].name]
                                v2 = g.v[e._v[1].name]
                                if e.__class__.__name__ == 'UndirEdge':
                                    g.add_e(UndirEdge(len(g.e),v1,v2))
                                elif e.__class__.__name__ == 'DirEdge':
                                    g.add_e(DirEdge(len(g.e),v1,v2))

                    return g



#!/usr/bin/env python

'''Class to automate delegation decisions based on inheritance graph.

Copyright 2004, Robert Dick (dickrp@ece.northwestern.edu).

Whenever you need to delegate to something, inherit from delegate and use
self.__<base>.<method()> to access the base.  If the delegation was
inappropriate due to reconverging paths in the inheritance graph, the return
value will be None.  In the case of reconverging paths, the left-most call in
the method resolution order will be honored.  The rest will be nulified.  You
can also check to see if the base is the no_delegation object.  Delegate to all
your bases if you need everything in the inheritance graph to be visited.  As
long as one of a class's (transitive) bases inherits from Delegate, that's
enough.

For examples of use, please see the delegate.py file.

Python doesn't yet automate meta-class instantiation.  If you need to inherit
from Delegate and another class that does not have a 'type' metaclass, you'll
need to generate a shared derived metaclass and explicitly use that as your
class's metaclass.  For example:

    import Delegate, qt

    class sip_meta_join(type(Delegate), type(qt.QObject)):
    def __init__(*args):
        type(Delegate).__init__(*args)
        type(qt.QObject).__init__(*args)

    class MyClass(Delegate, qt.QObject):
    __metaclass__ = sip_meta_join
    ...

Please see the license at the end of the source code for legal information.'''


__version__ = '0.1'
__author__ = 'Robert Dick (dickrp@ece.northwestern.edu)'


def should_call(obj, pos, supr):
            '''Returns bool.  Should 'self' delegate to 'super' at 'pos'?

            Determines whether pos is left-most derived of super in MRO.'''

            for c in type(obj).__mro__:
                    if supr in c.__bases__:
                                return pos is c
            return False

class _no_delegation(object):
            '''All class's attributes are null callable's.'''

            _to_base = set(['__bases__', '__name__', '__mro__', '__module__'])

            def __getattribute__(self, attr):
                    if attr in _no_delegation._to_base:
                                return getattr(object, attr)
                    def no_action(*pargs, **kargs): pass
                    return no_action

'''Whatever'''
no_delegation = _no_delegation()
'''Whatever'''


class _delegate_meta(type):

        '''Sets up delegation private variables.
        
        Traverses inheritance graph on class construction.  Creates a private
        __base variable for each base class.  If delegating to the base class is
        inappropriate, uses _no_delegation class.'''
        
        def __init__(cls, name, bases, dict):
            type.__init__(cls, name, bases, dict)
            visited_supr = set()
            for sub in cls.__mro__[:-1]:
                subnm = sub.__name__.split('.')[-1]
                for supr in sub.__bases__:
                    suprnm = supr.__name__.split('.')[-1]
                    if supr not in visited_supr:
                        visited_supr.add(supr)
                        deleg = supr
                    else:
                        deleg = no_delegation
                        setattr(cls, '_%s__%s' % (subnm, suprnm), deleg)
                        

class Delegate(object):
            '''Inherit from Delegate to get delegation variables on class construction.'''
            __metaclass__ = _delegate_meta


if __name__ == '__main__':
    class Base(Delegate):
        def __init__(self, basearg):
            self.__Delegate.__init__(self)
            self.basearg = basearg
            print 'base'
            
        def __str__(self): return 'BASE'
        

    class Left(Base):
        def __init__(self, basearg, leftarg):
            self.__Base.__init__(self, basearg)
            self.leftarg = leftarg
            print 'left'

        def __str__(self):
            return ' '.join(filter(None, (self.__Base.__str__(self), 'LEFT')))


    class Right(Base):
        def __init__(self, basearg):
            self.__Base.__init__(self, basearg)
            print 'right'

        def __str__(self):
            return ' '.join(filter(None, (self.__Base.__str__(self), 'RIGHT')))


    class Der(Left, Right):
        def __init__(self, basearg, leftarg):
            self.__Left.__init__(self, basearg, leftarg)
            self.__Right.__init__(self, basearg)
            print 'der'

        def __str__(self):
            return ' '.join(filter(None, (self.__Left.__str__(self),
                                          self.__Right.__str__(self), 'DER')))
        

    print 'should print base, left, right, der'
    der = Der('basearg', 'leftarg')
    
    print '\nshould print base, left'
    left = Left('basearg', 'leftarg')

    print '\nshould print base right'
    right = Right('basearg')
    
    print '\nshould print BASE LEFT RIGHT DER'
    print der



a4297a12f323bcaafa48fce5362885fabc430fb0
#!/usr/bin/env python

'''Directed and undirected graph data structures and algorithms.

Copyright 2004, Robert Dick (dickrp@ece.northwestern.edu).
Please see the license at the end of the source code for legal information.'''

__version__ = '0.2'
__author__ = 'Robert Dick (dickrp@ece.northwestern.edu)'


import copy, new, operator, struct, delegate

# The following four lines borrowed from Gregory R. Warnes's fpconst
# (until it's standard in Python distributions).
if struct.pack('i',1)[0] != '\x01':
    PosInf = struct.unpack('d', '\x7F\xF0\x00\x00\x00\x00\x00\x00')[0]
else:
    PosInf = struct.unpack('d', '\x00\x00\x00\x00\x00\x00\xf0\x7f')[0]


class GraphError(StandardError):
            '''Exception for graph errors.'''
            pass


class SortStruct(float, object):
            '''Throw-away class for temporarily holding values.

            Initialize with a float distance and as many keyword args as desired.
            The keyword args become attributes.'''

            def __new__(cls, val, **kargs):
                    obj = float.__new__(cls, val)
                    obj.__dict__ = kargs
                    return obj

            @property
            def number(self): return float(self)


def _condop(cond, v1, v2):
            if cond:
                    return v1
            else:
                    return v2

def _roprop(description = None):
            def prop_func(ro_method):
                    return property(ro_method, None, None, description)
            return prop_func

#================================================================================

class Vertex(delegate.Delegate):
            '''General graph vertex.

            All methods colaborate with directed and undirected
            edges.  If the edges are undirected, ine == oute.

            Variables :
            --------------------
                self._e = list of edges of this vertex
                self.in_e = list of incoming edges (decorator)
                self.out_e = list of outgoing edges (decorator)
                self.all_e = list of all edges = self._e (decorator)

            '''

            def attach_e(self, e):
                    '''Attach an edge.'''
                    self._e.append(e)

            def connecting_e(self, v):
                    '''List of edges connecting self and other vertex.'''
                    return [e for e in self._e if e.leaves(self) and e.enters(v)]

            def __init__(self, name):
                    '''Name neen't be a string but must be hashable and immutable.'''
                    self.__Delegate.__init__(self)
                    self._e = []
                    self.name = name

            def __str__(self): return str(self.name)

            def __getstate__(self):
                    '''Need to break cycles to prevent recursion blowup in pickle.

                    Dump everything except for edges.'''
                    dcp = copy.copy(self.__dict__)
                    dcp['_e'] = []
                    return dcp

            @_roprop('All edges.')
            def all_e(self): return self._e

            @_roprop('Incoming edges.')
            def in_e(self): return [e for e in self._e if e.enters(self)]

            @_roprop('Outgoing edges.')
            def out_e(self): return [e for e in self._e if e.leaves(self)]

            @_roprop('Set of adjacent vertices.  Edge direction ignored.')
            def adjacent_v(self):
                    adj = set(v for e in self._e for v in e.all_v)
                    try: adj.remove(self)
                    except: pass
                    return adj

            @_roprop('Set of vertices connected by incoming edges.')
            def in_v(self):
                    return set(v for e in self._e for v in e.src_v if e.enters(self))

            @_roprop('Set of vertices connected by outgoing edges.')
            def out_v(self):
                    return set(v for e in self._e for v in e.dest_v if e.leaves(self))

            @_roprop('True if vertex has no outgoing edges.')
            def is_sink(self): return not self.out_e

            @_roprop('True if vertex has no incoming edges.')
            def is_src(self): return not self.in_e

            @_roprop('True if vertex has incoming and outgoing edges.')
            def is_intermed(self): return not self.is_sink and not self.is_src

            def __eq__(a,b):
                return hash(a) == hash(b)

#===========================================================================

class RawEdge(delegate.Delegate):
            '''Base class for undirected and directed edges.  Not directly useful.'''

            def __init__(self, name, v1, v2):
                    '''Name needn't be a string but must be immutable and hashable.'''
                    self.__Delegate.__init__(self)
                    self.name = name
                    self._v = [v1, v2]
                    v1.attach_e(self)
                    v2.attach_e(self)

            def __setstate__(self, state):
                    '''Restore own state and add self to connected vertex edge lists.'''
                    self.__dict__ = state
                    self._v[0].attach_e(self)
                    self._v[1].attach_e(self)

            @_roprop('All connected vertices.')
            def all_v(self): return self._v


class UndirEdge(RawEdge):
            '''Undirected edge.'''

            def enters(self, v):
                    '''True if this edge is connected to the vertex.'''
                    return v in self._v

            def leaves(self, v):
                    '''True if this edge is connected to the vertex.'''
                    return v in self._v

            def __str__(self):
                    return '%s: %s -- %s' % (str(self.name), str(self._v[0]),
                                str(self._v[1]))

            def weight(self, v1, v2):
                    '''1 if this edge connects the vertices.'''
                    if v1 not in self._v or v2 not in self._v:
                                raise GraphError('vertices not connected')
                    return 1

            @_roprop('Source vertices.')
            def src_v(self): return self._v

            @_roprop('Destination vertices.')
            def dest_v(self): return self._v


class DirEdge(RawEdge):
            '''Directed edge.

                Variables :
                --------------
                self._v[0] = source vertex
                self._v[1] = destination vertex
            '''

            def enters(self, v):
                    '''True only if the vertex is this edge's destination.'''
                    return v is self._v[1]

            def leaves(self, v):
                    '''True only if the vertex is this edge's source.'''
                    return v is self._v[0]

            def invert(self):
                    '''Inverts the edge direction.'''
                    self._v.reverse()

            def weight(self, v1, v2):
                    '''1 if this edge has v1 as its source and v2 as its destination.'''
                    if v1 is not self._v[0] or v2 is not self._v[1]:
                                raise GraphError('vertices not connected')
                    return 1

            def __str__(self):
                    return '%s: %s -> %s' % (str(self.name), str(self._v[0]),
                                str(self._v[1]))

            @_roprop(
                    '''Single element list containing the edge's source vertex.

                    Must be a list to conform with UndirEdge's interface.''')
            def src_v(self): return [self._v[0]]

            @_roprop(
                    '''Single element list containing the edge's destination vertex.

                    Must be a list to conform with UndirEdge's interface.''')
            def dest_v(self): return [self._v[1]]

#================================================================================

def DataWrapped(cls):
            '''Returns a wrapped class with a new 'data' member.'''

            class __Wr(cls):
                    '''Wrapper to add 'data' to another class.'''

                    def __init__(self, *pargs, **kargs):
                                '''Use last parg for data and sends all other args to base.'''
                                if kargs:
                                            cls.__init__(self, *pargs[:-1], **kargs)
                                else:
                                            cls.__init__(self, *pargs[:-1])
                                self.data = pargs[-1]

                    def __str__(self):
                                '''Append data to base's __str__.'''
                                return ' '.join(filter(None, (cls.__str__(self), str(self.data))))

            __Wr.__name__ = 'Data%s' % cls.__name__.split('.')[-1]
            return __Wr

DataVertex = DataWrapped(Vertex)
DataUndirEdge = DataWrapped(UndirEdge)
DataDirEdge = DataWrapped(DirEdge)

#================================================================================

class VertexDict(dict, delegate.Delegate):
            '''Dictionary of vertices.'''

            def __init__(self, graph):
                    self.__dict.__init__(self)
                    self.__Delegate.__init__(self)
                    self.graph = graph

            def __setitem__(self, key, val):
                    if self.has_key(key):
                                raise KeyError('VertexDict already has (%s, %s).' % (key, val))
                    self.__dict.__setitem__(self, key, val)

            def __delitem__(self, key):
                    '''Delete all edges connected to the vertex, along with the vertex.'''
                    v = self[key]
                    for e in reversed(v._e):
                                del self.graph.e[e.name]
                    self.__dict.__delitem__(self, key)


class EdgeDict(dict, delegate.Delegate):
            '''Dictionary of edges.'''

            def __setitem__(self, key, val):
                    if self.has_key(key):
                                raise KeyError('EdgeDict already has (%s, %s).' % (key, val))
                    self.__dict.__setitem__(self, key, val)

            def __delitem__(self, key):
                    '''Remove edge from vertices to which it is attached.'''
                    e = self[key]
                    for v in e._v:
                                v._e.remove(e)
                    self.__dict.__delitem__(self, key)

#================================================================================

class Graph(delegate.Delegate):
            '''General-purpose graph data structure.'''

            def __init__(self, name = None):
                    self.name = name
                    self.v = VertexDict(self)
                    self.e = EdgeDict()

            def __str__(self):
                    return self.__class__.__name__ + \
                                _condop(self.name, ' ' + str(self.name), '') + '\nVertices:\n' + \
                                '\n'.join([str(v) for v in self.v.values()]) + \
                                '\n\nEdges:\n' + \
                                '\n'.join([str(e) for e in self.e.values()]) + '\n'




            @_roprop('List of all vertices.')
            def all_v(self): return [v for n, v in self.v.items()]

            @_roprop('List of all vertices without incoming edges.')
            def src_v(self): return [v for n, v in self.v.items() if v.is_src]

            @_roprop('List of all vertices without outgoing edges.')
            def sink_v(self): return [v for n, v in self.v.items() if v.is_sink]

            @_roprop(
                    'List of all vertices with both incoming and outgoing edges.')
            def intermed_v(self):   return [v for n, v in self.v.items() if v.is_intermed]

            def add_v(self, v):
                    '''Add and return a vertex.'''
                    self.v[v.name] = v
                    return v

            def add_e(self, e):
                    '''Add and return an edge.'''
                    self.e[e.name] = e
                    return e

            def del_e(self, e):
                    '''delete an edge (e is the name of the edge)'''
                    assert(self.e.has_key(e)), "The edge is not in the BNet"
                    del self.e[e]

            def connex_components(self):
                """ returns a list of list of nodes that are connected between
                 them"""
                unchecked = set(self.v.values())
                groups = []
                while len(unchecked):
                            vcon = self.member_family(unchecked.pop())
                            unchecked -= set(vcon)
                            groups.append(set(vcon))
                return groups
                    
            def member_family(self, node):
                unprocessed = [node]
                visited = []
                while unprocessed:
                            v = unprocessed.pop()
                            if v not in visited:
                                        visited.append(v)
                                        unprocessed.extend(v.out_v)
                                        unprocessed.extend(v.in_v)
                return visited                

            def connected_components(self):
                    '''Return a list of lists.  Each holds transitively-connected vertices.'''
                    unchecked = set(self.v.values())
                    groups = []
                    while len(unchecked):
                                vcon = self.depth_first_search(unchecked.pop())
                                unchecked -= set(vcon)
                                groups.append(vcon)
                    return groups

            @staticmethod
            def depth_first_search(start_v):
                    '''Return a depth-first search list of vertices.'''
                    unprocessed = [start_v]
                    visited = []
                    while unprocessed:
                                v = unprocessed.pop()
                                if v not in visited:
                                            visited.append(v)
                                            unprocessed.extend(v.out_v)
                    return visited

            @staticmethod
            def breadth_first_search(start_v):
                    '''Return a breadth-first search list of vertices.'''
                    unprocessed = [start_v]
                    visited = []
                    while unprocessed:
                                v = unprocessed.pop(0)
                                if v not in visited:
                                            visited.append(v)
                                            unprocessed.extend(v.out_v)
                    return visited

            #@staticmethod
            def topological_sort(self):
                '''Return a topological sort list of vertices.'''
                # unprocessed is a list of all nodes that have no parents
                unprocessed = [v for v in self.v.values() if not v.in_v]
                
                return Graph.topological_sort_by_node(unprocessed)

            @staticmethod
            def topological_sort_by_node(start_v):
                '''Return a topological sort list of vertices.'''
                unprocessed = start_v
                visited = []
                while unprocessed:
                    v = unprocessed.pop(0)
                    incoming_v = v.adjacent_v - v.out_v
                    if v not in visited and not (incoming_v - set(visited)):
                        visited.append(v)
                        unprocessed.extend(v.out_v)
                return visited

            def HasNoCycles(self, start_v):
                ''' Return True if the node start_v is not in a cycle
                '''
                unprocessed = [start_v]
                visited = []
                result = True
                i = 0
                while unprocessed:
                            i += 1
                            v = unprocessed.pop(0)
                            if i ==1:
                                unprocessed.extend(v.out_v)
                            elif start_v in visited:
                                result = False
                                break
                            elif v not in visited:
                                visited.append(v)
                                unprocessed.extend(v.out_v)
                return result

##            def HasNoCycles(self, start_v):
##                ''' Return True if the node start_v is not in a cycle
##                '''
##                unprocessed = [start_v]
##                visited = []
##                result = True
##                i = 0
##                while unprocessed:
##                            i += 1
##                            v = unprocessed.pop(0)
##                            if v not in visited:
##                                visited.append(v)
##                                unprocessed.extend(v.out_v)
##                            else:
##                                result = False
##                                break
##                return result

#================================================================================

            def minimal_span_tree(self, **kargs):
                    '''Return minimal spanning 'Tree'.

                    Keyword arg 'weight_func' is a function taking (edge, v1, v2) and
                    returning a weight.  Defaults to e.weight().
                    'targets' list of target vertices.  Defaults to all vertices.'''

                    def def_weight_func(e, v1, v2): return e.weight(v1, v2)
                    weight_func = kargs.get('weight_func', def_weight_func)
                    targets = kargs.get('targets', self.v.values())
                    visited = set([targets.pop()])
                    unvisited = set(self.v.values()) - visited
                    mst = Tree()

                    while targets:
# Haven't found it yet.  Search more.
                                connected = []
                                for v in visited:
                                            for u in unvisited:
                                                    conn = v.connecting_e(u)
                                                    if conn:
                                                                dist = weight_func(conn.pop(), v, u)
                                                                connected.append(SortStruct(dist, src=v, dest=u))

                                if not connected:
                                            raise GraphError('unreachable vertices in minimal_spanning_tree')

# Connect it
                                near = min(connected)
                                if near.src.name not in mst.v:
                                            mst.add_v(DataVertex(near.src.name, near.src))
                                if near.dest.name not in mst.v:
                                            mst.add_v(DataVertex(near.dest.name, near.src))
                                e = mst.auto_add_e(DirEdge(len(mst.e), mst.v[near.src.name],
                                            mst.v[near.dest.name]))

                                visited.add(near.dest)
                                unvisited.remove(near.dest)
                                targets.remove(near.dest)
                    return mst

#================================================================================

            def shortest_tree(self, start, **kargs):
                    '''Return a 'Tree' of shortest paths to all nodes.

                    Keyword arg 'weight_func' is a function taking (edge, v1, v2) and
                    returning a weight.  Defaults to e.weight().
                    'targets' list of target vertices.  Defaults to all vertices.'''

                    def def_weight_func(e, v1, v2): return e.weight(v1, v2)
                    weight_func = kargs.get('weight_func', def_weight_func)
                    targets = set(kargs.get('targets', self.v.values()))
                    path_tr = Tree()
                    dist = {start:0.0}
                    unvisited = set(self.v.values())
                    while targets:
# Determine the closest vertex
                                closest = min([(dist.get(v, PosInf), v) for v in unvisited])[1]
# Add it and push the distances
                                unvisited.remove(closest)
                                targets.discard(closest)
                                adj_v = closest.out_v
                                if not adj_v - unvisited:
                                            raise GraphError('unreachable vertices in shortest_tree')
                                for v in adj_v:
                                            for e in closest.connecting_e(v):
                                                    push_dist = weight_func(e, closest, v) + dist[closest]
                                                    if push_dist < dist.get(v, PosInf):
                                                                dist[v] = push_dist
# Add the vertices.  Remove the old edges, if any.  Add the new edge.
                                                                if closest.name not in path_tr.v:
                                                                            path_tr.add_v(DataVertex(closest.name, closest))
                                                                if v.name not in path_tr.v:
                                                                            path_tr.add_v(DataVertex(v.name, v))
                                                                e_nm = len(path_tr.e)
                                                                for e2 in path_tr.v[v.name].in_e:
                                                                            del path_tr.e[e2.name]
                                                                            e_nm = e2.name
                                                                path_tr.auto_add_e(DirEdge(e_nm, path_tr.v[closest.name],
                                                                            path_tr.v[v.name]))
                    return path_tr

#================================================================================

            def greedy_paths(self, start, goal, weight_func = None):
                    '''Return a dict of greedy paths with (start vertex, end vertex) keys.

                    Always makes the highest-gain decision.  Will find a path if one exists.
                    Not necessarily optimal.  'weight_func' is a function of (edge, v1, v2)
                    returning a weight.  Defaults to e.weight()'''

                    def def_weight_func(e, v1, v2): return e.weight(v1, v2)
                    weight_func = weight_func or def_weight_func
                    path = [start]
                    visited = set([start])
                    while path[-1] is not goal:
                                adj_v = [SortStruct(weight_func(e, path[-1], v), dest=v)
                                            for e in path[-1].out_e for v in e.dest_v if v not in visited]
                                if adj_v:
                                            closest_v = min(adj_v).dest
                                            visited.add(closest_v)
                                            path.append(closest_v)
                                else:
                                            path.pop()
# Prepare the dict
                    d = {}
                    for i1 in range(len(path)):
                                for i2 in range(i1, len(path)):
                                            d[path[i1], path[i2]] = path[i1:i2 + 1]
                    return d

            def all_pairs_sp(self, weight_func = None):
                    '''Return a dictionary of shortest path lists for all vertex pairs.

                    Keys are (source, destination) tuples.
                    'weight_func' is a function taking (edge, v1, v2) that returns a weight.
                    Defaults to e.weight()'''

                    return dict(self.shortest_tree(v,
                                weight_func=weight_func).path_dict().items() for v in self.v.values())

#================================================================================

            @staticmethod
            def path_weight(path, weight_func = None):
                    '''Return the weight of the path, which is a list of vertices.

                    'weight_func' is a function taking (edge, v1, v2) and returning a weight.'''

                    def def_weight_func(e, v1, v2): return e.weight(v1, v2)
                    weight_func = weight_func or def_weight_func
                    wt = 0.0
                    for v1, v2 in zip(path[:-1], path[1:]):
                                connect_e = [e for e in v1.out_e if e.enters(v2)]
                                if not connect_e:
                                            raise GraphError('vertices in path are not connected')
                                wt += min(weight_func(e, v1, v2) for e in connect_e)
                    return wt

#================================================================================
#================================================================================
#                   MY CODE !!!!!!!!!!!!!!! (Kostas Gaitanis)
#================================================================================
#================================================================================




class TreeError(GraphError): pass

class Tree(Graph):
            '''Tree data structure.

            Edges must be directed and reconvergent paths do not occur.'''

            def add_e(self, e):
                    '''Add edge if tree invariant holds.  Otherwise, raise exception.'''
                    if len(e.dest_v) != 1:
                                raise TreeError('undirected edge')
                    if len(e.dest_v[0].in_e) != 1:
                                raise TreeError('edge introduces reconvergent paths into tree')
                    return self.__Graph.add_e(self, e)

            def auto_add_e(self, e):
                    '''Automatically choose correct direction for new edge.'''
                    if len(e.dest_v) != 1:
                                raise TreeError('undirected edge')
                    if len(e.dest_v[0].in_e) != 1:
                                e.invert()
                    self.add_e(e)

            def is_safe_e(self, target_v):
                    '''True if edge maintains tree invariant.'''
                    return not target_v.in_e

            def path_dict(self):
                    '''Return a dictionary of path lists from the root to each vertex.

                    Keys are (source vertex, destination vertex) tuples.'''

                    root = self.src_v
                    assert len(root) == 1
                    root = root.pop()

                    d = {(root.data, root.data):[root.data]}
                    for v in self.depth_first_search(root):
                                parent = v.in_v
                                assert len(parent) <= 1
                                if parent:
                                            parent = parent.pop()
                                            d[root.data, v.data] = d[root.data, parent.data] + [v.data]
                    return d

#################################################################################
if __name__ == '__main__':
            G = Graph()
            a, b, c, d, e, f, g = [G.add_v(BVertex(nm)) for nm in 'a b c d e f g'.split()]
            for ep in [(a, b), (a, c), (b, d), (b, f), (b, e), (c, e), (d, f), (e, f),
            (f, g)]:
                    G.add_e(UndirEdge(len(G.e), *ep))

            print G
            #print 'DFS:', map(str, G.depth_first_search(a))
            #print 'BFS:', map(str, G.breadth_first_search(a))
            #print 'top sort:', map(str, G.topological_sort(a))

            #T = G.minimal_span_tree()
            #print T
            #print [(map(str, k), map(str, v)) for k, v in T.path_dict().items()]

            #S = G.shortest_tree(a)
            #print S

            print a



            ###################################################################
            # just in case, this is the copy method I created, but don't seem to need it
            ######################################
            def __copy__(self):
                    g = Graph('Copy of ' + str(self.name))

                    # copy vertices
                    for v in self.v.values():
                                if v.__class__.__name__ == 'BVertex':
                                            g.add_v(BVertex(v.name, v.nvalues))
                                elif v.__class__.__name__ == 'Vertex':
                                            g.add_v(Vertex(v.name))


                    # for each edge, create a corresponding edge in g
                    for e in self.e.values():
                                print e
                                print e._v[0].name
                                v1 = g.v[e._v[0].name]
                                v2 = g.v[e._v[1].name]
                                if e.__class__.__name__ == 'UndirEdge':
                                    g.add_e(UndirEdge(len(g.e),v1,v2))
                                elif e.__class__.__name__ == 'DirEdge':
                                    g.add_e(DirEdge(len(g.e),v1,v2))

                    return g



#!/usr/bin/env python

'''Class to automate delegation decisions based on inheritance graph.

Copyright 2004, Robert Dick (dickrp@ece.northwestern.edu).

Whenever you need to delegate to something, inherit from delegate and use
self.__<base>.<method()> to access the base.  If the delegation was
inappropriate due to reconverging paths in the inheritance graph, the return
value will be None.  In the case of reconverging paths, the left-most call in
the method resolution order will be honored.  The rest will be nulified.  You
can also check to see if the base is the no_delegation object.  Delegate to all
your bases if you need everything in the inheritance graph to be visited.  As
long as one of a class's (transitive) bases inherits from Delegate, that's
enough.

For examples of use, please see the delegate.py file.

Python doesn't yet automate meta-class instantiation.  If you need to inherit
from Delegate and another class that does not have a 'type' metaclass, you'll
need to generate a shared derived metaclass and explicitly use that as your
class's metaclass.  For example:

    import Delegate, qt

    class sip_meta_join(type(Delegate), type(qt.QObject)):
    def __init__(*args):
        type(Delegate).__init__(*args)
        type(qt.QObject).__init__(*args)

    class MyClass(Delegate, qt.QObject):
    __metaclass__ = sip_meta_join
    ...

Please see the license at the end of the source code for legal information.'''


__version__ = '0.1'
__author__ = 'Robert Dick (dickrp@ece.northwestern.edu)'


def should_call(obj, pos, supr):
            '''Returns bool.  Should 'self' delegate to 'super' at 'pos'?

            Determines whether pos is left-most derived of super in MRO.'''

            for c in type(obj).__mro__:
                    if supr in c.__bases__:
                                return pos is c
            return False

class _no_delegation(object):
            '''All class's attributes are null callable's.'''

            _to_base = set(['__bases__', '__name__', '__mro__', '__module__'])

            def __getattribute__(self, attr):
                    if attr in _no_delegation._to_base:
                                return getattr(object, attr)
                    def no_action(*pargs, **kargs): pass
                    return no_action

'''Whatever'''
no_delegation = _no_delegation()
'''Whatever'''


class _delegate_meta(type):

        '''Sets up delegation private variables.
        
        Traverses inheritance graph on class construction.  Creates a private
        __base variable for each base class.  If delegating to the base class is
        inappropriate, uses _no_delegation class.'''
        
        def __init__(cls, name, bases, dict):
            type.__init__(cls, name, bases, dict)
            visited_supr = set()
            for sub in cls.__mro__[:-1]:
                subnm = sub.__name__.split('.')[-1]
                for supr in sub.__bases__:
                    suprnm = supr.__name__.split('.')[-1]
                    if supr not in visited_supr:
                        visited_supr.add(supr)
                        deleg = supr
                    else:
                        deleg = no_delegation
                        setattr(cls, '_%s__%s' % (subnm, suprnm), deleg)
                        

class Delegate(object):
            '''Inherit from Delegate to get delegation variables on class construction.'''
            __metaclass__ = _delegate_meta


if __name__ == '__main__':
    class Base(Delegate):
        def __init__(self, basearg):
            self.__Delegate.__init__(self)
            self.basearg = basearg
            print 'base'
            
        def __str__(self): return 'BASE'
        

    class Left(Base):
        def __init__(self, basearg, leftarg):
            self.__Base.__init__(self, basearg)
            self.leftarg = leftarg
            print 'left'

        def __str__(self):
            return ' '.join(filter(None, (self.__Base.__str__(self), 'LEFT')))


    class Right(Base):
        def __init__(self, basearg):
            self.__Base.__init__(self, basearg)
            print 'right'

        def __str__(self):
            return ' '.join(filter(None, (self.__Base.__str__(self), 'RIGHT')))


    class Der(Left, Right):
        def __init__(self, basearg, leftarg):
            self.__Left.__init__(self, basearg, leftarg)
            self.__Right.__init__(self, basearg)
            print 'der'

        def __str__(self):
            return ' '.join(filter(None, (self.__Left.__str__(self),
                                          self.__Right.__str__(self), 'DER')))
        

    print 'should print base, left, right, der'
    der = Der('basearg', 'leftarg')
    
    print '\nshould print base, left'
    left = Left('basearg', 'leftarg')

    print '\nshould print base right'
    right = Right('basearg')
    
    print '\nshould print BASE LEFT RIGHT DER'
    print der


