Forecaster component:

    df = read_csv(CSV_FILE)

    #print(df)

    #print(df.groupby(['source', 'destination']).count())

    devices = dict()

    links = dict()

    #df1.groupby(['A','B']).size().reset_index().rename(columns={0:'count'})

    df_links = df[['link_id', 'source', 'destination']].drop_duplicates()

    for row in df_links.itertuples(index=False):

        #print(row)

        link_uuid = row.link_id

        src_device_uuid = row.source

        dst_device_uuid = row.destination

        src_port_uuid = row.destination

        dst_port_uuid = row.source

        if src_device_uuid not in devices:

            devices[src_device_uuid] = {'id': src_device_uuid, 'endpoints': set()}

        devices[src_device_uuid]['endpoints'].add(src_port_uuid)

        if dst_device_uuid not in devices:

            devices[dst_device_uuid] = {'id': dst_device_uuid, 'endpoints': set()}

        devices[dst_device_uuid]['endpoints'].add(dst_port_uuid)

        if link_uuid not in links:

            links[link_uuid] = {

                'id': link_uuid,

                'src_dev': src_device_uuid, 'src_port': dst_device_uuid,

                'dst_dev': dst_device_uuid, 'dst_port': src_device_uuid,

            }

    links = df.groupby(['source', 'destination']).all()

    for link in links:

        print(link)

if __name__ == '__main__':

    main()