def graph_to_ank(network, graph, asn=None, include_ext_nodes=True):
""" Converts a GML graph from the Zoo into AutoNetkit compatible graph"""
# Default label
if not 'Network' in graph.graph:
graph.graph['Network'] = "Network"
# if no asn set, use next available
#TODO: put this into a function which returns a graph for combining at the
# end
LOG.debug("passed in asn of %s " % asn)
if graph.is_multigraph():
graph = nx.DiGraph(graph)
if 'Network' in graph.graph:
LOG.info(("Converting {0} to single-edge graph").format(
graph.graph['Network']))
else:
LOG.info("Converting to single-edge graph")
# ANK uses directed graphs
graph = graph.to_directed()
#TODO: see if ASN set in the graph
asn_list = ank.nodes_by_as(network).keys()
LOG.debug("current ASN list %s " % asn_list)
# And append any ASNs manually specified
manual_asn = {}
for node, data in graph.nodes(data=True):
if ('type' in data and data['type'].startswith("AS") and
data['type'][2:].isdigit()):
# This node has a valid manually specified ASN
node_asn = int(data['type'][2:])
manual_asn[node] = node_asn
# Unique
manual_asn_unique = list(set(manual_asn.keys()))
for node_asn in manual_asn_unique:
if node_asn in asn_list:
LOG.warn("Manually specified ASN %i already in use" % asn)
# Record these as in use
asn_list += manual_asn_unique
LOG.debug("asn list after adding manual uniques %s " % asn_list)
# Allocate asns
# Find next free asn
def next_unallocated_asn():
LOG.debug("nua fn asn list %s " % asn_list)
if len(asn_list) > 0:
nua = max(asn_list)
while nua in asn_list:
try:
nua += 1
except TypeError as e:
LOG.warn("Unable to set Next Unallocated ASN %i to ASN list"
" %s " % (nua, asn_list))
asn_list.append(nua)
return nua
else:
# No asn in use
nua = 1
asn_list.append(nua)
return nua
#TODO: clean up this logic
if asn and asn in asn_list:
# User specified asn already in use
LOG.warn("ASN %s already in use" % asn)
elif asn:
# Record as being used
asn_list.append(int(asn))
# Record name for DNS
network.as_names[asn] = graph.graph['Network']
else:
# No asn set, use next available
asn = next_unallocated_asn()
# and record
network.as_names[asn] = graph.graph['Network']
#TODO: check that writing using names doesn't overwrite the same folder
# eg may have 5 AARNET nodes, but all overwrite same folder in nk lab
# If multiple external nodes with same name, merge into single node
# TODO: make this behaviour able to be turned on/off
# eg either merge, keep, make unique, or remove, depending on how
# external names combined
#TODO: use include_external_nodes
external_nodes = [node for node in graph.nodes()
if ('Internal' in
graph.node[node] and
graph.node[node]['Internal'] == 0)]
# Group external nodes by their name
ext_node_dict = defaultdict(list)
for node in external_nodes:
if not include_ext_nodes:
graph.remove_node(node)
else:
label = graph.node[node]['label']
ext_node_dict[label].append(node)
# Now merge nodes
for label, nodes in ext_node_dict.items():
if len(nodes) > 1:
# Multiple nodes for this label, merge
# Choose the first (arbitary) node to merge others into
primary_node = nodes.pop()
for node in nodes:
# merge remaining nodes into primary node
# get edges from this node
#TODO: look at using edges_iter here
for src, dst, data in graph.edges(node,
data=True):
# add link from primary
graph.add_edge(primary_node, dst, data)
# and reverse link
graph.add_edge(dst, primary_node, data)
graph.remove_node(node)
for node in graph:
if node in manual_asn:
# Node has ASN manually specified (as previously determined)
graph.node[node]['asn'] = manual_asn[node]
elif ('Internal' in graph.node[node]):
if graph.node[node]['Internal'] == 1:
graph.node[node]['asn'] = asn
elif graph.node[node]['Internal'] == 0:
graph.node[node]['asn'] = next_unallocated_asn()
else:
# No internal/external set, assume all internal nodes
graph.node[node]['asn'] = asn
# Check labels are unique
# Store nodes by their label, duplicates are labels with more than one node
nodes_by_label = defaultdict(list)
all_labels = set()
for node, data in graph.nodes_iter(data=True):
nodes_by_label[data['label']].append(node)
all_labels.add(data['label'])
duplicates = ( (label, nodes) for (label, nodes) in nodes_by_label.items()
if len(nodes) > 1)
for (label, nodes) in duplicates:
if label == '':
label = "Untitled"
for index, node in enumerate(nodes):
node_label = "%s_%s" % (label, index)
if node_label in all_labels:
# TODO: throw error
print "Node label %s already used " % node_label
else:
all_labels.add(node_label)
graph.node[node]['label'] = node_label
#TODO: log to debug the changed label name
#TODO: check no blank labels
#TODO: put this into general algorithms module
#TODO: replace with helper methods to return fqdn and folder names
return graph
