Import DyNetML into Python, NetworkX, and igraph

dynetml2other provides an importer and a set of wrapper classes for DyNetML files that allow them to be used with several Python graph libraries. These wrapper classes also support exporting data in DyNetML format, meaning that it can be created, used with this package, and then save out for analysis with other tools.

The current way to use the module is by giving the dynetml2other method the path to the file you want to parse:

>>> from dynetml2other import dynetml2other
>>> dmn_with_graphs_as_networkx = dynetml2other('path_to_dynamic_metanetwork_from_twitter.xml', 'networkx')
>>> dmn_with_graphs_as_igraphs = dynetml2other('path_to_dynamic_metanetwork_from_twitter.xml', 'igraph')
>>> dmn_with_graphs_as_dicts = dynetml2other('path_to_dynamic_metanetwork_from_twitter.xml')
>>> dmn_with_graphs_as_dicts
<dynetml2other.DynamicMetaNetwork.DynamicMetaNetwork instance at 0x10e857950>
>>> mn_with_graphs_as_dicts = dynetml2other('vanilla_metanetwork_for_some_project.xml')
>>> mn_with_graphs_as_dicts
<dynetml2other.MetaNetwork.MetaNetwork instance at 0x10e857098>
>>> dmn_with_graphs_as_dicts.attributes
{'id': 'Twitter JSON - 1 Hour'}
>>> dmn_with_graphs_as_dicts[0]
<dynetml2other.MetaNetwork.MetaNetwork instance at 0x10e857cb0>
>>> len(dmn_with_graphs_as_dicts.metanetworks
23
>>> dmn_with_graphs_as_dicts.metanetworks[0].attributes
{'date': '20130503T10:00:00', 'id': '2013-05-03 10 AM'}
>>> dmn_with_graphs_as_dicts.metanetworks[0].propertyIdentities
{'importFile': ('text', False), 'importLastTweetDate': ('date', False), 'lastTweetDate': ('dat
e', False), 'importAggregationPeriod': ('text', False), 'importFirstTweetDate': ('date', False
), 'firstTweetDate': ('date', False), 'importFileFormat': ('text', False)}
>>> dmn_with_graphs_as_dicts.write_dynetml('a_copy_of_the_dynetml.xml')

To define the method properly:

Imports a DyNetML file into a wrapper class that uses NetworkX, igraph, or Python dictionaries to contain the networks.

dynetml2other.main(dynetml_path, network_format='dict')[source]
Parameters:
  • dynetml_path (str|unicode) – Path to a dynetml file
  • network_format (str|unicode) – The network format; we expect “networkx”, “igraph”, or nothing (“dict”)
Returns:

The data wrapped in the appropriate class and stored in the specified graph library

Return type:

DynamicMetaNetwork|MetaNetwork|None

If the file contains a meta-network, and based on t will be parsed into an instance of MetaNetwork, which stores graph data in dictionaries, or into one of its SubClasses:

If the file contains a dynamic meta-network, it will be parsed into a instance of DynamicMetaNetwork, which contains a list of MetaNetworks or of one of MetaNetwork’s SubClasses. Types of MetaNetworks cannot be mixed within a DynamicMetaNetwor.

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