#!/usr/bin/env python
"""
========
Football
========

Load football network in GML format and compute some network statistcs.

Shows how to download GML graph in a zipped file, unpack it, and load
into a NetworkX graph.

Requires Internet connection to download the URL
http://www-personal.umich.edu/~mejn/netdata/football.zip
"""
# Author: Aric Hagberg (hagberg@lanl.gov)

#    Copyright (C) 2007-2019 by
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
#    All rights reserved.
#    BSD license.

try:  # Python 3.x
    import urllib.request as urllib
except ImportError:  # Python 2.x
    import urllib
import io
import zipfile

import matplotlib.pyplot as plt
import networkx as nx

url = "http://www-personal.umich.edu/~mejn/netdata/football.zip"

sock = urllib.urlopen(url)  # open URL
s = io.BytesIO(sock.read())  # read into BytesIO "file"
sock.close()

zf = zipfile.ZipFile(s)  # zipfile object
txt = zf.read('football.txt').decode()  # read info file
gml = zf.read('football.gml').decode()  # read gml data
# throw away bogus first line with # from mejn files
gml = gml.split('\n')[1:]
G = nx.parse_gml(gml)  # parse gml data

print(txt)
# print degree for each team - number of games
for n, d in G.degree():
    print('%s %d' % (n, d))

options = {
    'node_color': 'black',
    'node_size': 50,
    'line_color': 'grey',
    'linewidths': 0,
    'width': 0.1,
}
nx.draw(G, **options)
plt.show()