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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 graph_from_polygon(polygon, network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, name='unnamed', timeout=180, memory=None, max_query_area_size=50*1000*50*1000, clean_periphery=True, infrastructure='way["highway"]', custom_filter=None):
 """ Create a networkx graph from OSM data within the spatial boundaries of the passed-in shapely polygon. Parameters polygon : shapely Polygon or MultiPolygon the shape to get network data within. coordinates should be in units of latitude-longitude degrees. network_type : string what type of street network to get simplify : bool if true, simplify the graph topology retain_all : bool if True, return the entire graph even if it is not connected truncate_by_edge : bool if True retain node if it's outside bbox but at least one of node's neighbors are within bbox name : string the name of the graph timeout : int the timeout interval for requests and to pass to API memory : int server memory allocation size for the query, in bytes. If none, server will use its default allocation size max_query_area_size : float max size for any part of the geometry, in square degrees: any polygon bigger will get divided up for multiple queries to API clean_periphery : bool if True (and simplify=True), buffer 0.5km to get a graph larger than requested, then simplify, then truncate it to requested spatial extent infrastructure : string download infrastructure of given type (default is streets (ie, 'way["highway"]') but other infrastructures may be selected like power grids (ie, 'way["power"~"line"]')) custom_filter : string a custom network filter to be used instead of the network_type presets Returns ------- networkx multidigraph """


    # verify that the geometry is valid and is a shapely Polygon/MultiPolygon
    # before proceeding
    if not polygon.is_valid:
        raise TypeError('Shape does not have a valid geometry')
    if not isinstance(polygon, (Polygon, MultiPolygon)):
        raise TypeError('Geometry must be a shapely Polygon or MultiPolygon. If you requested '
                         'graph from place name or address, make sure your query resolves to a '
                         'Polygon or MultiPolygon, and not some other geometry, like a Point. '
                         'See OSMnx documentation for details.')

    if clean_periphery and simplify:
        # create a new buffered polygon 0.5km around the desired one
        buffer_dist = 500
        polygon_utm, crs_utm = project_geometry(geometry=polygon)
        polygon_proj_buff = polygon_utm.buffer(buffer_dist)
        polygon_buffered, _ = project_geometry(geometry=polygon_proj_buff, crs=crs_utm, to_latlong=True)

        # get the network data from OSM,  create the buffered graph, then
        # truncate it to the buffered polygon
        response_jsons = osm_net_download(polygon=polygon_buffered, network_type=network_type,
                                          timeout=timeout, memory=memory,
                                          max_query_area_size=max_query_area_size,
                                          infrastructure=infrastructure, custom_filter=custom_filter)
        G_buffered = create_graph(response_jsons, name=name, retain_all=True,
                                  bidirectional=network_type in settings.bidirectional_network_types)
        G_buffered = truncate_graph_polygon(G_buffered, polygon_buffered, retain_all=True, truncate_by_edge=truncate_by_edge)

        # simplify the graph topology
        G_buffered = simplify_graph(G_buffered)

        # truncate graph by polygon to return the graph within the polygon that
        # caller wants. don't simplify again - this allows us to retain
        # intersections along the street that may now only connect 2 street
        # segments in the network, but in reality also connect to an
        # intersection just outside the polygon
        G = truncate_graph_polygon(G_buffered, polygon, retain_all=retain_all, truncate_by_edge=truncate_by_edge)

        # count how many street segments in buffered graph emanate from each
        # intersection in un-buffered graph, to retain true counts for each
        # intersection, even if some of its neighbors are outside the polygon
        G.graph['streets_per_node'] = count_streets_per_node(G_buffered, nodes=G.nodes())

    else:
        # download a list of API responses for the polygon/multipolygon
        response_jsons = osm_net_download(polygon=polygon, network_type=network_type,
                                          timeout=timeout, memory=memory,
                                          max_query_area_size=max_query_area_size,
                                          infrastructure=infrastructure, custom_filter=custom_filter)

        # create the graph from the downloaded data
        G = create_graph(response_jsons, name=name, retain_all=True,
                         bidirectional=network_type in settings.bidirectional_network_types)

        # truncate the graph to the extent of the polygon
        G = truncate_graph_polygon(G, polygon, retain_all=retain_all, truncate_by_edge=truncate_by_edge)

        # simplify the graph topology as the last step. don't truncate after
        # simplifying or you may have simplified out to an endpoint beyond the
        # truncation distance, in which case you will then strip out your entire
        # edge
        if simplify:
            G = simplify_graph(G)

    log('graph_from_polygon() returning graph with {:,} nodes and {:,} edges'.format(len(list(G.nodes())), len(list(G.edges()))))
    return G