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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def create_graph(response_jsons, name='unnamed', retain_all=False, bidirectional=False):
 """ Create a networkx graph from OSM data. Parameters response_jsons : list list of dicts of JSON responses from from the Overpass API name : string the name of the graph retain_all : bool if True, return the entire graph even if it is not connected bidirectional : bool if True, create bidirectional edges for one-way streets Returns ------- networkx multidigraph """


    log('Creating networkx graph from downloaded OSM data...')
    start_time = time.time()

    # make sure we got data back from the server requests
    elements = []
    for response_json in response_jsons:
        elements.extend(response_json['elements'])
    if len(elements) < 1:
        raise EmptyOverpassResponse('There are no data elements in the response JSON objects')

    # create the graph as a MultiDiGraph and set the original CRS to default_crs
    G = nx.MultiDiGraph(name=name, crs=settings.default_crs)

    # extract nodes and paths from the downloaded osm data
    nodes = {}
    paths = {}
    for osm_data in response_jsons:
        nodes_temp, paths_temp = parse_osm_nodes_paths(osm_data)
        for key, value in nodes_temp.items():
            nodes[key] = value
        for key, value in paths_temp.items():
            paths[key] = value

    # add each osm node to the graph
    for node, data in nodes.items():
        G.add_node(node, **data)

    # add each osm way (aka, path) to the graph
    G = add_paths(G, paths, bidirectional=bidirectional)

    # retain only the largest connected component, if caller did not
    # set retain_all=True
    if not retain_all:
        G = get_largest_component(G)

    log('Created graph with {:,} nodes and {:,} edges in {:,.2f} seconds'.format(len(list(G.nodes())), len(list(G.edges())), time.time()-start_time))

    # add length (great circle distance between nodes) attribute to each edge to
    # use as weight
    if len(G.edges) > 0:
        G = add_edge_lengths(G)

    return G