/usr/share/pyshared/tracspamfilter/filters/bayes.py is in trac-spamfilter 0.2.1+svn6871-4.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 | # -*- coding: utf-8 -*-
#
# Copyright (C) 2005-2006 Edgewall Software
# Copyright (C) 2005 Matthew Good <trac@matt-good.net>
# Copyright (C) 2006 Christopher Lenz <cmlenz@gmx.de>
# All rights reserved.
#
# This software is licensed as described in the file COPYING, which
# you should have received as part of this distribution. The terms
# are also available at http://trac.edgewall.com/license.html.
#
# This software consists of voluntary contributions made by many
# individuals. For the exact contribution history, see the revision
# history and logs, available at http://projects.edgewall.com/trac/.
#
# Author: Matthew Good <trac@matt-good.net>
from math import ceil
import re
from pkg_resources import parse_version
from trac import __version__ as VERSION
from trac.config import IntOption
from trac.core import *
from trac.db import DatabaseManager
from trac.wiki.api import IWikiChangeListener
from trac.wiki.model import WikiPage
from tracspamfilter.api import IFilterStrategy
from spambayes.hammie import Hammie
from spambayes.storage import SQLClassifier
class BayesianFilterStrategy(Component):
"""Bayesian filtering strategy based on SpamBayes."""
implements(IFilterStrategy)
karma_points = IntOption('spam-filter', 'bayes_karma', '10',
"""By what factor Bayesian spam probability score affects the overall
karma of a submission.""")
min_training = IntOption('spam-filter', 'bayes_min_training', '25',
"""The minimum number of submissions in the training database required
for the filter to start impacting the karma of submissions.""")
# IFilterStrategy implementation
def test(self, req, author, content):
hammie = self._get_hammie()
nspam = hammie.bayes.nspam
nham = hammie.bayes.nham
if min(nspam, nham) < self.min_training:
self.log.info('Bayes filter strategy requires more training. '
'It currently has only %d words marked as ham, and '
'%d marked as spam, but requires at least %d for '
'each.', nham, nspam, self.min_training)
return
if nham - nspam > min(nham, nspam) * 2:
self.log.warn('The difference between the number of ham versus '
'spam submissions in the training database is large, '
'results may be bad.')
score = hammie.score(content.encode('utf-8'))
self.log.debug('SpamBayes reported spam probability of %s', score)
points = -int(round(self.karma_points * (score * 2 - 1)))
if points != 0:
return points, 'SpamBayes determined spam probability of %.2f%%' % (
score * 100)
def train(self, req, author, content, spam=True):
self.log.info('Training SpamBayes, marking content as %s',
spam and 'spam' or 'ham')
hammie = self._get_hammie()
hammie.train(content.encode('utf-8', 'ignore'), spam)
hammie.store()
# Internal methods
def _get_hammie(self):
return Hammie(TracDbClassifier(self.env.get_db_cnx()))
def _get_numbers(self):
hammie = self._get_hammie()
return hammie.nspam, hammie.nham
class TracDbClassifier(SQLClassifier):
# FIXME: This thing is incredibly slow
def __init__(self, db):
self.db = db
SQLClassifier.__init__(self, 'Trac')
def load(self):
if self._has_key(self.statekey):
row = self._get_row(self.statekey)
self.nspam = row['nspam']
self.nham = row['nham']
else: # new database
self.nspam = self.nham = 0
def _sanitize(self, text):
"""Remove invalid byte sequences from utf-8 encoded text"""
if isinstance(text, unicode):
return text
return text.decode('utf-8', 'ignore')
def _get_row(self, word):
word = self._sanitize(word)
cursor = self.db.cursor()
cursor.execute("SELECT nspam,nham FROM spamfilter_bayes WHERE word=%s",
(word,))
row = cursor.fetchone()
if not row:
return {}
return {'nspam': row[0], 'nham': row[1]}
def _set_row(self, word, nspam, nham):
word = self._sanitize(word)
cursor = self.db.cursor()
if self._has_key(word):
cursor.execute("UPDATE spamfilter_bayes SET nspam=%s,nham=%s "
"WHERE word=%s", (nspam, nham, word))
else:
cursor.execute("INSERT INTO spamfilter_bayes (word,nspam,nham) "
"VALUES (%s,%s,%s)", (word, nspam, nham))
self.db.commit()
def _delete_row(self, word):
word = self._sanitize(word)
cursor = self.db.cursor()
cursor.execute("DELETE FROM spamfilter_bayes WHERE word=%s", (word,))
self.db.commit()
def _has_key(self, key):
key = self._sanitize(key)
cursor = self.db.cursor()
cursor.execute("SELECT COUNT(*) FROM spamfilter_bayes WHERE word=%s",
(key,))
return bool(cursor.fetchone()[0])
def _wordinfoget(self, word):
# See http://mail.python.org/pipermail/spambayes-dev/2006-July/003684.html
row = self._get_row(word)
if row:
item = self.WordInfoClass()
item.__setstate__((row["nspam"], row["nham"]))
return item
else:
return None
def _wordinfokeys(self):
cursor = self.db.cursor()
cursor.execute("SELECT word FROM spamfilter_bayes")
return [row[0] for row in cursor.fetchall()]
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