68 lines
1.7 KiB
Python
Executable File
68 lines
1.7 KiB
Python
Executable File
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import sqlite3
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import networkx as nx
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from pyvis.network import Network
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import matplotlib.pyplot as plt
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from datetime import datetime
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def retrieve_traceroute_data():
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conn = sqlite3.connect('traceroute.db')
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cursor = conn.cursor()
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cursor.execute('''
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SELECT l.source_ip, l.destination_ip, ll.latency_ms, ll.timestamp
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FROM Latency ll
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JOIN links l ON ll.link_id = l.id
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ORDER BY ll.timestamp
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''')
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rows = cursor.fetchall()
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conn.close()
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return rows
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def build_graph(data):
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G = nx.DiGraph() # Create a directed graph
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for row in data:
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source_ip = row[0]
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destination_ip = row[1]
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latency = row[2]
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timestamp = row[3]
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# Add nodes and edges to the graph
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G.add_node(source_ip)
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G.add_node(destination_ip)
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G.add_edge(source_ip, destination_ip, latency=latency, timestamp=timestamp)
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return G
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#def visualize_graph_pyvis(G, output_file='network.html'):
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# net = Network(height='750px', width='100%', directed=True)
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# net.from_nx(G)
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#
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# for edge in G.edges(data=True):
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# src, dst, data = edge
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# latency = data['latency']
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# timestamp = data['timestamp']
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# net.add_edge(src, dst, title=f'Latency: {latency} ms<br>Timestamp: {timestamp}', value=latency)
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#
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# net.show(output_file)
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def main():
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# Retrieve data from the database
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traceroute_data = retrieve_traceroute_data()
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# Build the network graph
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graph = build_graph(traceroute_data)
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return graph
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if __name__ == '__main__':
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graph = main()
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nx.draw_planar(graph, with_labels=True)
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plt.savefig("path.png")
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# Visualize the graph using pyvis
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#visualize_graph_pyvis(graph, 'traceroute_network.html')
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#exit(0)
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