Converts a dict representing an OLSR 0.6.x topology
        to a NetworkX Graph object, which is then returned.
        Additionally checks for "config" data in order to determine version and revision.

def parse(self, data):
        """
        Converts a dict representing an OLSR 0.6.x topology
        to a NetworkX Graph object, which is then returned.
        Additionally checks for "config" data in order to determine version and revision.
        """
        graph = self._init_graph()
        if 'topology' not in data:
            raise ParserError('Parse error, "topology" key not found')
        elif 'mid' not in data:
            raise ParserError('Parse error, "mid" key not found')

        # determine version and revision
        if 'config' in data:
            version_info = data['config']['olsrdVersion'].replace(' ', '').split('-')
            self.version = version_info[1]
            # try to get only the git hash
            if 'hash_' in version_info[-1]:
                version_info[-1] = version_info[-1].split('hash_')[-1]
            self.revision = version_info[-1]

        # process alias list
        alias_dict = {}
        for node in data['mid']:
            local_addresses = [alias['ipAddress'] for alias in node['aliases']]
            alias_dict[node['ipAddress']] = local_addresses

        # loop over topology section and create networkx graph
        for link in data['topology']:
            try:
                source = link['lastHopIP']
                target = link['destinationIP']
                cost = link['tcEdgeCost']
                properties = {
                    'link_quality': link['linkQuality'],
                    'neighbor_link_quality': link['neighborLinkQuality']
                }
            except KeyError as e:
                raise ParserError('Parse error, "%s" key not found' % e)
            # add nodes with their local_addresses
            for node in [source, target]:
                if node not in alias_dict:
                    continue
                graph.add_node(node, local_addresses=alias_dict[node])
            # skip links with infinite cost
            if cost == float('inf'):
                continue
            # original olsrd cost (jsoninfo multiplies by 1024)
            cost = float(cost) / 1024.0
            # add link to Graph
            graph.add_edge(source, target, weight=cost, **properties)
        return graph