s4:auth_winbind: remove unused 'winbind_wbclient' backend
[Samba.git] / script / traffic_learner
blobfd5affd609b14bebf36f673ee74202fcf9a7c86a
1 #!/usr/bin/env python
2 # Generate a traffic model from a traffic summary file
4 # Copyright (C) Catalyst IT Ltd. 2017
6 # This program is free software; you can redistribute it and/or modify
7 # it under the terms of the GNU General Public License as published by
8 # the Free Software Foundation; either version 3 of the License, or
9 # (at your option) any later version.
11 # This program is distributed in the hope that it will be useful,
12 # but WITHOUT ANY WARRANTY; without even the implied warranty of
13 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
14 # GNU General Public License for more details.
16 # You should have received a copy of the GNU General Public License
17 # along with this program. If not, see <http://www.gnu.org/licenses/>.
20 import sys
21 import argparse
23 sys.path.insert(0, "bin/python")
24 from samba.emulate import traffic
27 def main():
28 parser = argparse.ArgumentParser(description=__doc__,
29 formatter_class=argparse.RawDescriptionHelpFormatter)
30 parser.add_argument('-o', '--out', type=argparse.FileType('w'),
31 help="write model here")
32 parser.add_argument('--dns-mode', choices=['inline', 'count'],
33 help='how to deal with DNS', default='count')
34 parser.add_argument('SUMMARY_FILE', nargs='*', type=argparse.FileType('r'),
35 default=[sys.stdin],
36 help="read from this file (default STDIN)")
37 args = parser.parse_args()
39 if not args.out:
40 print >> sys.stdout, "No output file was specified to write the model to."
41 print >> sys.stdout, "Please specify a filename using the --out option."
42 return
44 if args.SUMMARY_FILE is sys.stdin:
45 print >> sys.stderr, "reading from STDIN..."
47 (conversations,
48 interval,
49 duration,
50 dns_counts) = traffic.ingest_summaries(args.SUMMARY_FILE,
51 dns_mode=args.dns_mode)
53 model = traffic.TrafficModel()
54 print >> sys.stderr, "learning model"
55 if args.dns_mode == 'count':
56 model.learn(conversations, dns_counts)
57 else:
58 model.learn(conversations)
60 model.save(args.out)
63 main()