The document discusses using Python and the NetworkX library to generate and analyze graphs. It shows how to import NetworkX, generate different types of graphs including paths, cycles, complete graphs and random graphs. It also demonstrates functions for analyzing graphs like calculating node degrees, edges, average path length and density. The document then discusses using the Twitter API via the Tweepy library to generate a follower graph in Python starting from a seed user.

2.  Basic Python
› Data types(Integer, String, List)
› Control flow statements
› List comprehension

3.  Import NetworkX
import networkx as nx
 Generating a graph
G = nx.Graph()
 Adding a node
G.add_node(“one”)
 Adding nodes
G.add_nodes_from([“two”, “three”])
 Adding an edge
G.add_edge(“one”, “two”)
 Adding edges
G.add_edges_from([(“two”, “three”), (“three”, “one”)])

4. import matplotlib.pyplot as plt
nx.draw(G)
plt.show()

5.  Path graphs
› G = nx.path_graph(40)
 Cycle graphs
› G = nx.cycle_graph(40)
 Complete graphs
› G = nx.complete_graph(40)
 2D grid graphs
› G = nx.grid_2d_graph(5, 4)
 Random graphs
› G = nx.erdos_renyi_graph(20, 0.3)
› G = nx.barabasi_albert_graph(100, 5)

7.  The number of degrees
› len(G.nodes())
 The number of edges
› len(G.edges())
 Average degree
› 2 * len(G.edges()) / len(G.nodes())
 Average path length
› Gsub = nx.connected_component_subgraphs(G)[0]
› nx.average_shortest_path_length(G)
 Network density
› nx.density(G)

8. deg = [nx.degree(G,n) for n in G.nodes()]
hist = [0 for i in range(max(deg)+1)]
for d in deg:
hist[d] += 1
plt.plot(range(len(hist)), hist, "or")
plt.show()

10.  Go to http://apps.twitter.com and create your app .
› You will get API Key, API Secret, Access Token, and Access Token Secret.
 Installing tweepy
› pip install tweepy

11.  Next, many, many lines of python code
 You can get the python script(named
Tweepy1.py) at
https://codebreak.com/git/arity/TweepyTutori
al/tree/master/

12. import time
import tweepy
# Copy the api key, the api secret, the access token and the access
# token secret from the relevant page on your Twitter app
api_key = ‘your_api_key_here'
api_secret = ‘your_api_secret_here’
access_token = ‘your_access_token_here'
access_token_secret = ‘your_access_token_secret_here'
# You don't need to make any changes below here
# This bit authorises you to ask for information from Twitter
auth = tweepy.OAuthHandler(api_key, api_secret)
auth.set_access_token(access_token, access_token_secret)
# The api object gives you access to all of the http calls that Twitter accepts
api = tweepy.API(auth)

13. def fib(n,user,network):
if n>0:
time.sleep(40)
try:
users=api.followers(user)
except tweepy.TweepError:
return
for follower in users:
network.add_node(follower.screen_name)
network.add_edge(follower.screen_name, user)
fib(n-1,follower.screen_name,network)

14. #Then, There is a directed graph
G = nx.DiGraph()
#User we want to use as initial node
user='GitHub‘
G.add_node(user)
n=2
fib(n,user,G)
nx.draw(G)
plt.show()

16.  Graph manipulating functions
› Adding nodes, edges
 Many types of network
 Many network characteristics