61 lines
1.8 KiB
Python
Executable File
61 lines
1.8 KiB
Python
Executable File
#!/usr/bin/env python3
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from collections import defaultdict
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from datetime import datetime
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from node_ranking import (
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parse_csv,
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csv_loader,
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build_graph,
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Node,
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)
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def load_data(path):
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data = defaultdict(list)
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with open(path, 'r') as f:
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for line in f.readlines():
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when = datetime.strptime(line.split(',')[0]+'00', '%Y-%m-%d %H:%M:%S%z')
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data[when].append(
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parse_csv(line, source_ip_index=1, source_port_index=2, dest_ip_index=3, dest_port_index=4)
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)
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return data
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def main():
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data = load_data('./part-dist-edges.csv')
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print(f'loaded data. {len(data.keys())} buckets')
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for bucket, edges in data.items():
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edges = list(edges)
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print(f'bucket: {bucket}')
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print(f'edges: {len(edges)}')
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g = build_graph(edges)
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count_map = {}
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for node in g:
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count_map[node.node] = len(list(g.successors(node)))
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sum_out = 0
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known = Node('34.204.196.211', 9796)
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for v in count_map.values():
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sum_out += v
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min_out = min(count_map.items(), key=lambda kv: kv[1])
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max_out = max(count_map.items(), key=lambda kv: kv[1])
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avg_out = float(sum_out) / len(count_map.keys())
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known_out = count_map[known]
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print(f'\tavg_out: {avg_out}')
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print(f'\tmin_out: {min_out}')
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print(f'\tmax_out: {max_out}')
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print(f'\tknown_out: {known} {known_out}')
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with open(f'./avg_out/{bucket.timestamp()}.txt', 'w') as out:
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out.write(f'bucket: {bucket}\n')
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out.write(f'\tavg_out: {avg_out}\n')
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out.write(f'\tmin_out: {min_out}\n')
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out.write(f'\tmax_out: {max_out}\n')
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out.write(f'\tknown_out: {known} {known_out}\n')
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if __name__ == "__main__":
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main()
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